Reagentless analysis of biological samples

ABSTRACT

Apparatus and method for determining at least one parameter, e. g., concentration, of at least one analyte, e. g., urea, of a biological sample, e. g., urine. A biological sample particularly suitable for the apparatus and method of this invention is urine. In general, spectroscopic measurements can be used to quantify the concentrations of one or more analytes in a biological sample. In order to obtain concentration values of certain analytes, such as hemoglobin and bilirubin, visible light absorption spectroscopy can be used. In order to obtain concentration values of other analytes, such as urea, creatinine, glucose, ketones, and protein, infrared light absorption spectroscopy can be used. The apparatus and method of this invention utilize one or more mathematical techniques to improve the accuracy of measurement of parameters of analytes in a biological sample. The invention also provides an apparatus and method for measuring the refractive index of a sample of biological fluid while making spectroscopic measurements substantially simultaneously.

This application is division of application Ser. No. 09/141,483, filedAug. 27, 1998, now U.S. Pat. No. 6,087,182.

BACKGROUND OF THE INVENTION

1. Field of the Invention

This invention relates to the field of analysis of biological samples,both solids and liquids, e. g., urinalysis, and, in particular, toapparatus and method for conducting analysis of biological sampleswithout the need for reagents. This invention also relates to detectionof adulteration of samples of biological fluid to protect the integrityof analysis results.

2. Discussion of the Art

Determining the concentration of an analyte or a parameter of physicalcondition in a biological sample has been an important area in the fieldof diagnostics. Analytes that have diagnostic value includes nutrients,metabolites, enzymes, immunity entities, hormones, and pathogens. Thephysical characteristics of a biological sample, such as temperature,optical properties, density, and hardness, are also of interest becauseof their capability of providing indications for diagnostic purposes.Most determination methods use signal-enhancing agents.

Urinalysis involves measuring critical components in a sample of urineto determine the condition of the body with respect to diseases andother substances, e. g., drugs. Urine contains a wide variety ofsubstances. In current urinalysis systems, such as those provided byBayer and Boehringer Mannheim, the analytes measured include glucose,bilirubin, ketones (80% 3-hydroxybutyrate, 17% acetoacetic acid, 3%acetone), blood (or hemoglobin), protein, urobilinogen, nitrites, andleukocytes. Specific gravity (or refractive index) and pH are alsomeasured. In some cases, measurement of creatinine is suggested, but isnot provided by Bayer's or Boehringer Mannheim's urinalysis systems. Allof these analytes represent breakdown products of metabolism fromvarious organ systems. The pattern of excretion is indicative of variousdisease states. The history and utility of urinalysis is discussed inVoswinckel, Peter, “A marvel of colors and ingredients. The story ofurine test strips”, Kidney International, Vol. 46, Suppl. 47 (1994), pp.S-3-S-7, and Free, Alfred H. & Free, Helen M., “Urinalysis: Its ProperRole in the Physician's Office”, Office Practice of Laboratory Medicine,Clinics in Laboratory Medicine—Vol. 6, No. 2, June 1986, both of whichare incorporated herein by reference.

Urinalysis testing is also used as a means to determine which samples ofurine need to be examined by microscopy, which is such an expensive andtime-consuming procedure that it cannot be performed on all urinesamples with current methods. Microscopic examination of urine sedimentcan confirm the presence of bacterial infection, or white cells,indicating infection or kidney damage, among other indications.

The majority of urinalysis testing is accomplished by means of dip andread strip technology supplied by Bayer and Boehringer Mannheim. Striptechnology is well understood and suffers from a number of limitations.Readings must be properly timed to obtain accurate results. Controlsmust be employed. Urine samples must be well mixed and at roomtemperature. Strips are sensitive to light and humidity, and must bestored and handled properly. Quantitative results are difficult toobtain. Interfering substances can cause incorrect readings.

Abuse of drugs and other substances is recognized as a significantproblem in the United States, and is now being recognized in other partsof the world. As a result, more people are being tested in routine drugscreening programs than ever before. In the United States, about 10% ofthe population is estimated to abuse drugs or alcohol, and about 70% ofthose are employed. Business and government organizations in the UnitedStates will spend about $725,000,000 in 1998 to test selectedpopulations to determine whether their performance may be impaired byabuse of depressants, hallucinogens, hypnotics/sedatives, or stimulants.In most cases, the sample tested is urine. Consequences of failing aroutine drug screen can be severe, e. g., loss of employment or loss offreedom if testing is performed for the criminal justice system, andthese consequences have led to the development of an industry designedto “beat” a drug test. Drug testing can be “beaten” by simply dilutingthe sample with water, apple juice, or similar materials. Drug testingcan also be “beaten” by attacking the macromolecules and indicators usedin the testing systems with materials such as acids, bases, nitrites,and glutaraldehyde, among others.

While estimates of the extent of adulteration are difficult to obtainand some evidence suggests that they vary with the populations tested,estimates of adulteration range as high as 30% of urine samplessubmitted for testing. The drug of abuse assay system using EnzymeMultiplied Immunoassay Technique (EMIT) is a major high-speed screeningtool for drugs of abuse, but it is also among the most sensitive systemsto failures caused by sample adulteration. Systems based on fluorescencepolarization immunoassay (FPIA) are more robust, but are not immune fromfailures caused by adulterated samples.

To achieve the social purpose of deterring drug abuse by testing ofurine, it is essential to assure the integrity of the samples of urine.Sample integrity can be assured by “observed” collection. However, sucha stringent method is applicable only in special situations, and iscostly. Legal considerations require a thoroughly documented chain ofcustody for each sample. A system configuration that permits a check forsample adulteration and simultaneously sequesters the sample for furthertesting such as GC/mass spectrometry, or for archiving, may beadvantageous. The integrity of a urine sample can also be judged bymeasuring specific gravity, pH, creatinine level, and temperature of thesample before committing the sample to further tests that employ costlyreagents. Low levels of creatinine may indicate dilution of the sample.An abnormally low or high value of pH indicates the addition of acid orbase. Altered specific gravity indicates the addition of foreignmaterials, such as apple juice or salts, that may alter test results. Ifthe temperature of a urine sample is unexpectedly low, it may indicatethat a sample was substituted, and if the temperature of a urine sampleis unexpectedly high, it may indicate that a sample was substituted orthat a chemical reaction took place. By ensuring sample integrity,potentially adulterated samples may be rejected for testing, andunadulterated samples may be recollected more quickly, thereby assuringthe accuracy of the test results, and preventing impaired individualsfrom endangering the safety of the public.

There are several methods for measuring creatinine. The oldest, theJaffee method, requires temperature control for accurate results. The3,5-DiNitroBenzoic Acid (DNBA) method (similar to the Jaffee method) hasbeen adapted to strips for a serum assay. Both methods have beencommercialized with as many as four enzymes by Kodak. When measured withlong wavelength infrared radiation, creatinine provides the secondstrongest signal in urine. Hence, infrared spectroscopy utilizingmultivariate mathematical analysis is able to “pick-out” creatinine witha high degree of precision and specificity.

The amount of dissolved solids in urine is typically measured byrefractive index measurement (the gold standard) or by specific gravitymeasurements. Measurements of refractive index and specific gravity inurine are highly correlated, as shown by studies of samples of patientsin hospitals.

pH is a measure of acid or base content of the urine sample. Standardlaboratory practice makes use of a pH electrodes for accurate pHmeasurements. Miniature pH electrodes have been demonstrated by NovaBiomedical (Waltham, Mass.) in their instruments and by others. Bayerhas a block on a colorimetric strip that measures pH in urine withreasonable accuracy for the normal range of pH in urine (4.6-8.0).

It would be desirable to provide a method and a device for analysis ofbiological samples and detection of sample adulteration that does notencounter the disadvantages of a system based on reagent-containingstrips. In a reagentless system, the stability, storage, and shelf lifeissues of reagents would be of no concern. In a reagentless system, themethod could be automated and would not require precise timing by theuser. Interfering substances could be detected and incorrect readingscould be minimized. Proper controls could be incorporated into thesystem and could be transparent to the user. Quantitative readings couldbe performed better, and larger dynamic ranges than can be provided byreagent-containing strips could be made available. A reagentless systemhas the additional advantage that it can be adapted to possible futureexpansion of adulterants when the features of those adulterants becomeknown. If needed, a reagentless system could also be integrated with areagent-using system to provide a broader menu, better performance, andhigher throughput.

SUMMARY OF THE INVENTION

This invention provides an apparatus and method for determining at leastone parameter, e. g., concentration, of at least one analyte, e. g.,urea, of a biological sample, e. g., urine. A biological sampleparticularly suitable for the apparatus and method of this invention isurine. In general, spectroscopic measurements can be used to quantifythe concentrations of one or more analytes in a biological sample. Inorder to obtain concentration values of certain analytes, such ashemoglobin and bilirubin, visible light spectroscopy can be used. Inorder to obtain concentration values of other analytes, such as urea,creatinine, glucose, ketones, and protein, infrared light spectroscopycan be used. The apparatus and method of this invention utilize one ormore mathematical techniques to improve the accuracy of measurement ofparameters of analytes in a biological sample.

In one aspect, the invention provides a method for determining at leastone parameter of at least one analyte of a biological sample involvingthe use of a mathematical technique to assist in reducing noise insignal detection in spectroscopic measurements. More specifically, thisinvention provides a method for reducing noise in a determination ofconcentration of at least one analyte of interest in a biological sampleby means of spectroscopic analysis comprising the steps of:

(a) identifying a mathematical function that is substantially similar toa region of a non-smoothed spectrum of the sample over a selected rangeof the non-smoothed spectrum;

(b) selecting a portion of the region of the non-smoothed spectrum suchthat noise in the selected portion is substantially random;

(c) determining coefficients of the mathematical function that result ina close fit of the function to the selected portion of the non-smoothedspectrum;

(d) calculating at least one value of the non-smoothed spectrum at atleast one wavelength of the non-smoothed spectrum by means of thecoefficients and the mathematical function of step (c), wherein said atleast one wavelength includes the center of the region of thenon-smoothed spectrum;

(e) assigning said at least one calculated value of the non-smoothedspectrum to a wavelength including the center of the selected portion ofthe region of the non-smoothed spectrum to form at least one point of asmoothed spectrum;

(f) shifting a selected distance in the non-smoothed spectrum andrepeating steps (c), (d), and (e) until a desired amount of the smoothedspectrum is formed;

(g) forming a residual spectrum by subtracting each point of the desiredamount of the smoothed spectrum at a given wavelength from each point ofthe non-smoothed spectrum at said given wavelength;

(h) inspecting the residual spectrum to determine if it is random; and

(i) if the residual spectrum is not random, repeating steps (b), (c),(d), (e), (f), (g), and (h) to achieve a smoothing, wherein saidresidual spectrum is random.

In another aspect, the invention provides a method for determining atleast one parameter of at least one analyte of a biological sampleinvolving the use of a mathematical technique to assist in eliminationof residual signal associated with interfering compounds by the use ofmultivariate analysis, such as partial least squares. More specifically,this invention provides a method for determining concentration of atleast one analyte of interest in a biological sample of an individual bymeans of spectroscopic analysis comprising the steps of:

(a) identifying at least one analyte that is a major component of saidbiological sample, said at least one analyte accounting for significantvariations with respect to a plurality of spectra of biological samplesfrom a plurality of donors of said biological samples;

(b) measuring a spectrum for each of the plurality of biological samplesfrom the plurality of donors of the biological samples;

(c) calculating a model spectrum for each of the plurality of biologicalsamples from the plurality of donors of the biological samples bymathematically fitting spectra of the analytes of the at least oneidentified analyte to each spectrum of each of the biological samplesfrom the plurality of donors of the biological samples;

(d) calculating a residual spectrum for each spectrum of each of thebiological samples from the plurality of donors of the biologicalsamples by subtracting each value of the model spectrum from each valueof the spectrum of the biological samples from the plurality of donorsof the biological samples that corresponds to the model spectrum;

(e) repeating steps (a), (b), (c), and (d) at least one time byintroducing at least one additional analyte to the model spectrum untilthe calculated residual spectra are substantially constant from onebiological sample to another biological sample of the plurality ofbiological samples from the plurality of donors of the biologicalsamples;

(f) determining a set of calibration parameters from the model spectra,said set of calibration parameters accounting for effects of saidsubstantially constant residual spectra; and

(g) using said calibration parameters to determine concentration of ananalyte of interest in the sample of biological fluid of the individual.

By use of one or more of these mathematical techniques, a calibrationmodel can be derived. The calibration model and constants associatedwith the calibration model can be used to calculate the concentration ofan analyte of interest in a biological sample.

In another aspect, the invention provides a method for measuring therefractive index of a sample of biological fluid while makingspectroscopic measurements substantially simultaneously. The refractiveindex measurement provides the equivalent to a measurement of specificgravity, because both measurements are affected by the amount of solutein a solution. In this invention, however, the beam of light formeasuring the refractive index is not co-linear with the beam of lightfor spectroscopic measurements. Further, pH electrodes can be used toobtain accurate pH values of a sample of biological fluid. An ionselective electrode can be used to provide nitrite values of a sample ofbiological fluid when nitrites are present at low concentration, whileinfrared spectroscopy can be used to provide nitrite values of a sampleof biological fluid when nitrites are present at higher concentration.

If the spectroscopic measurements previously mentioned are combined witha cell counting method, such as flow cytometry, a fully integrated,rapid system for determining at least one parameter of at least oneanalyte of interest in a biological fluid as well as at least oneparameter of at least one particulate material in a sample of biologicalfluid can be constructed. Such a system can provide enhanced automationof systems that are now only partially automated.

In order to make it possible to carry out the foregoing methods in anoptimal manner, systems utilizing several novel components have beendeveloped. To aid in enhancing measurements of refractive index, it hasbeen found that a position-sensitive detector is preferred. Such adetector is commercially available. An arrangement for aligning thelight source with the sample and the position-sensitive detector hasbeen designed. To aid in enhancing the speed and convenience of carryingout spectroscopic measurements and refractive index measurements, asample cell assembly having a unique geometry has been designed. Inaddition, in some cases, it is desirable to employ assays that employreagents to enhance the accuracy of the reagentless system describedherein. For this purpose a system that integrates the reagentless systemof this invention with a reagent-using device has been developed. Theintegration of a reagent-using system with the reagentless system ofthis invention makes it possible to carry out determinations on analytesof interest that exhibit little or no spectral signature.

In a preferred embodiment of this invention, the system described hereincan be used to measure creatinine, pH, and refractive index to check foradulteration of urine in a drugs-of-abuse testing environment. Forspectroscopic measurements, it is preferred to employ a spectrometer,which measures the spectra of analytes of interest in a sample ofbiological fluid. In another preferred embodiment of this invention, thespectrometer previously mentioned can be replaced by a filter photometerunit, which involves utilization of appropriate filters to provideabsorbance values at selected wavelength regions of a spectrum ofinterest. Regardless of which type of instrument is used to determinethe spectrum, the preferred embodiments of this invention include thefollowing components:

(1) spectrometer or infrared filter photometer unit to measure theconcentration of creatinine in a sample of urine, whereby sampledilution brought about by ingestion of water or by direct dilution withother materials can be assessed;

(2) pH electrodes to assess the suitability of the sample for chemistryassays;

(3) refractometer to measure the level of dissolved solids.

Such a system may be expanded to include measurement of otheradulterants, such as glutaraldehyde and nitrites. Measurement ofadulterants can be simplified by selection of appropriate filters in aninfrared filter photometer.

An embodiment involving a hand-held or easily portable system that canserve the workplace testing area or insurance physicals area by allowingan immediate assessment of the integrity of a urine sample collected ina remote location is also contemplated. The system may include thefollowing components:

(1) laser diode or light emitting diode to measure the concentration ofcreatinine and other adulterants in a sample of urine, whereby thecreatinine value obtained can be used to assess dilution of samplecaused by ingestion of water or by direct dilution with water, whilepositive detection of other adulterants, such as glutaraldehyde ornitrites, can be used to identify urine samples spiked with suchadulterants,

(2) pH electrodes to assess the suitability of the sample for chemistryassays,

(3) refractometer to measure the level of dissolved solids,

(4) temperature sensor to determine if the sample is at aphysiologically significant temperature or whether a false sample hasbeen substituted.

Concentrations of components in a sample of urine are variable dependingon the state of hydration of the individual. By calculating the ratio ofthe concentration an analyte of interest in a urine sample (e. g.,ketones) to the concentration of creatinine, measurement variability canbe reduced or eliminated.

This invention provides several advantages over urinalysis systemscurrently in use. One of the problems for bilirubin determinations bymeans of test strips is caused by the stain of the reaction pad byurine, the color of which is too close to the color generated by thechemical reaction for bilirubin determination. This false positivesituation is of such concern that some laboratories routinely runconfirmatory tests. Because spectroscopic methods involve multiplewavelength differentiation, and do not generate a colored compound bychemical reaction, they do not suffer from the interference caused bythe native color of urine.

If integrated into an automatic analyzer system or if interfaced withthe ADx systems (an automated drug of abuse assay instrument by AbbottLaboratories), the reagentless system of this invention can provide adrug/creatinine ratio. The ratio can be used as a means to correct forsample dilution, and may represent a new standard in drugs of abusetesting.

The reagentless system of this invention provides improved performance,rapid throughput, elimination of reagents, and increased convenience forthe user. The reagentless system of this invention allows substantialremoval of base-line drift in spectroscopic measurements. Thereagentless system of this invention allows determination of theconcentrations of several analytes simultaneously in the presence ofinterfering signals in spectroscopic measurements.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic drawing of an analytical system capable ofproviding full menu capability and versatility for the practice of thisinvention.

FIG. 2 is a perspective view of an embodiment of an apparatus suitablefor use in this invention. In this embodiment, the unit for measuringthe spectrum is a spectrometer.

FIG. 3 is an exploded perspective view of the essential components ofthe unit employed in FIG. 2 for measuring the spectrum.

FIG. 4 is a perspective view of another embodiment of an apparatussuitable for use in this invention. In this embodiment, the unit formeasuring the spectrum is a filter photometer.

FIG. 5 is an exploded perspective view of the essential components ofthe unit shown in FIG. 4 for measuring the spectrum.

FIG. 6 is an exploded perspective view of the essential components of anassembly for determining refractive index of a sample of biologicalfluid.

FIG. 7 is perspective view of a sample cell assembly suitable for use inthis invention.

FIG. 8 is an exploded perspective view of the sample cell assembly shownin FIG. 7.

FIG. 9A is an enlarged elevational view of one embodiment of theinterior of the sample cell assembly shown in FIG. 7.

FIG. 9B is an enlarged elevational view of another embodiment of theinterior of the sample cell assembly shown in FIG. 7.

FIG. 10 is a schematic view of an arrangement for determining therefractive index of a biological fluid, wherein the sample-containingchamber of the sample cell assembly of this invention is in the form ofa prism. In this figure, the beams of light employed to determinerefractive index of a biological fluid are shown and characterized.

FIG. 11 is a schematic view of an arrangement for determining therefractive index of a biological fluid, wherein the entrance window ofthe sample-containing chamber of the sample cell assembly of thisinvention is curved.

FIG. 12 is a schematic view of an arrangement for determining therefractive index of a biological fluid, wherein a portion of thesample-containing chamber of the sample cell assembly is shown. In thisportion, the window where the light beam enters the chamber is parallelto the window where the light beam exits the chamber.

FIG. 13 is a graph showing spectra of both water and a sample of urine.

FIG. 14 is a graph showing spectra of urea, creatinine, glucose,albumin, ketones, and nitrites from a sample of urine after the spectrumof water has been subtracted.

FIG. 15 is a graph showing the derivative spectra of urea, creatinine,and glucose.

FIG. 16 is a graph showing the derivative spectra of albumin, nitrites,and ketones.

FIG. 17 is a graph showing the smoothed and non-smoothed spectra of ureaat a concentration of 200 mg/dL.

FIG. 18 is a graph showing the smoothed and non-smoothed spectra ofglucose at a concentration of 100 mg/dL.

FIG. 19 is a graph showing the smoothed and non-smoothed spectra ofalbumin at a concentration of 50 mg/dL.

FIG. 20 is a graph showing typical residual noise of a spectrum of ananalyte after the spectrum has been smoothed by means of a polynomialfunction.

FIG. 21 is a graph showing a typical smoothed spectrum of a sample ofurine.

FIG. 22 is a graph showing both the spectrum of a sample of urine and amodel spectrum consisting of the weighted spectra of six analytescommonly found in a urine sample.

FIG. 23 is a graph showing the residual spectra from four differentdonors of samples of urine.

FIG. 24 is a graph showing the performance of a spectroscopic assay forcreatinine.

FIG. 25 is a graph showing the relationship between specific gravity andrefractive index for normal urine samples. This graph was derived fromS. Bakhshandeh et al., “Michigan Medicine”, 74(21): 399-403, 1975),incorporated herein by reference.

FIG. 26 is a graph showing the relationship between a pH determinationby Bayer strips and a pH determination by pH electrodes.

FIG. 27 is a graph showing the performance of a spectroscopic assay forglutaraldehyde.

FIG. 28 is a graph showing the performance of a spectroscopic assay fornitrites.

FIG. 29 is a graph showing the performance of a spectroscopic assay forurea.

FIG. 30A is a schematic diagram illustrating a test tube containing abiological sample.

FIG. 30B is a schematic diagram illustrating dry reagent powder in asealed chamber in the cap of the test tube of FIG. 30A.

FIG. 30C is a schematic diagram illustrating a way of obtaining accessto the dry reagent by piercing the sealed membrane on the cap so thatthe dry reagent can reach the sample in the lower portion of the testtube.

FIG. 31 is a schematic diagram of a test tube having a plurality ofchambers for integrating the reagent-using option with the reagentlesssystem of this invention.

FIG. 32 is a graph showing the performance of a spectroscopic assay forbilirubin.

FIG. 33 is a graph showing the performance of a spectroscopic assay forhemoglobin.

DETAILED DESCRIPTION

As used herein, the expression “spectroscopic analysis” means analysisof a spectrum in order to determine characteristics of its source. Theterm “absorption” means the reduction of intensity of electromagneticradiation, according to Beer's Law, of a beam of electromagneticradiation as it propagates through a material. The expression“biological sample” is intended to include biological samples in solidform and biological samples in fluid form. For example, biologicalsamples in solid form include, but are not limited to, living bodyparts, such as, for example, fingers, ear lobes, forearms, internalorgans and the like, biopsy, tissue, skin, stool, and so forth.Biological sample in fluid form include, but are not limited to, urine,whole blood, plasma, serum, sputum, saliva, sweat, interstitial fluid,cerebral spinal fluid, and dialysate obtained in kidney dialysis, andthe like.

As used herein, the term “calibration” means the determination of amathematical function relating a physical quantity being measured to asignal measured. The term “prediction” refers to the calculation of theconcentration of an analyte in a given sample based on the signalsmeasured from the sample and the calibration determined from samplesindependent of the given sample.

As used herein, the expression “major component” refers to an analyte ofa biological sample that provides a signal that is substantially largerthan the background signal (i. e., the background signal excluding thecontribution of water). For example, in urinalysis, urea is a majorcomponent on account of its large spectral signature and highconcentration in urine. The expression “minor component” refers to ananalyte of a biological sample that provides a signal that is comparablein magnitude or smaller in magnitude than the background signal (i. e.,the background signal excluding the contribution of water). For example,in urinalysis, nitrites are considered a minor component, on account ofits low concentration in normal urine.

As used herein, the term “residual” means the remaining portion of ameasured quantity after a major portion of the measured quantity hasbeen accounted for. With respect to a spectral signal obtained from asample containing a multiplicity of components, the residual spectrum isthe portion of the spectral signal remaining after the portion of thespectral signal contributed by major components of the sample issubtracted from the observed spectrum. This residual spectrum of theobserved spectrum typically results from the presence of a combinationof minor components, which are usually interfering compounds. Forexample, in the case of urinalysis, it has been discovered herein thatthe residual portion of the spectral signal could be due to combinationof nitrites, salts, vitamins, metabolites, and hormonal metabolites thatare present at low concentrations. The term “model” means a tentativedescription of a theory or system that accounts for substantially all ofits known properties. The term “constant” means an experimental ortheoretical condition, factor, or quantity that occurs, is held, or isregarded as invariant in given circumstances. The term “noise” means ausually random and persistent disturbance that obscures or reduces theclarity or quality of a signal. The term “random” refers to a phenomenonhappening by chance, as in a haphazard manner. For example, a randomnoise is a variation in a signal that occurs by chance. Because thechance of the variation to be either higher or lower than the true valueis equal, the sum of the random noise (i. e., the difference of theobserved value from the true value) over an extended observationdimension (time, space, or wavelength) approached zero. The terms“smooth”, “smoothing”, and the like refer to elimination of random noisefrom a measured spectrum.

The term “reagentless” refers to a determination of a parameter of ananalyte of a biological sample without the use of a reagent. The term“reagent-using” means a method (in contrast to reagentless) wherechemical or biological agents are used for enhancing the process ofdetermining the presence or concentration of a specific analyte. Forexample, when an enzyme is used to react with a specific analyte togenerate a detectable signal for determination of that analyte, theenzyme is the reagent used for determination of that analyte, and thedetection method is a “reagent-using” method.

The expression “derivative spectroscopy” means either the process ofdetermining a derivative of a spectrum or the process of measuring aderivative spectrum directly by means of a derivative spectrometer.Derivative spectroscopy refers to the rate of change of the spectrumwith respect to the rate of change of wavelength. There can be manydifferent orders in derivative spectroscopy corresponding to thedifferent orders of derivatives in a mathematical function. For example,in first order derivative spectroscopy, the first derivative of theobserved spectrum is determined. The first derivative is equivalent tocalculating slope, as in obtaining the first derivative of amathematical function. See also Skoog and West, Principles ofInstrumental Analysis, Second Edition, Saunders College/Holt, Rinehartand Winston (Philadelphia:1980), pp.192-194, incorporated herein byreference.

The expression “base-line drift” means a slow varying trend of themeasured background in the detection system. The rate of change ofbase-line drift is lower than the rate of change of random noise.Base-line drift is typically caused by lamp warm up, temperature changein the system, or lamp aging.

As used herein, the term “light” means the subset of electromagneticradiation that includes the ultraviolet region of the electromagneticspectrum, the visible region of the electromagnetic spectrum, and theinfrared region of the electromagnetic spectrum. For example, radiowaves are not light waves.

As used herein, the ultraviolet region of the electromagnetic spectrumincludes light having a wavelength of from about 190 nm to about 400 nm.The visible region of the electromagnetic spectrum includes light havinga wavelength of from about 400 nm to about 780 nm. The infrared regionof the electromagnetic spectrum comprises the near-infrared region ofthe electromagnetic spectrum, the mid-infrared region of theelectromagnetic spectrum, and the far-infrared region of theelectromagnetic spectrum. The near-infrared region of theelectromagnetic spectrum includes light having a wavelength of fromabout 780 nm to about 1,500 nm; the mid-infrared region of theelectromagnetic spectrum includes light having a wavelength of fromabout 1,500 nm to about 3,000 nm; the far-infrared region of theelectromagnetic spectrum includes light having a wavelength of fromabout 3,000 nm to about 40,000 nm.

In one aspect, this invention involves a method for determining at leastone parameter, e. g., concentration, of an analyte of interest, e. g.,urea, in a sample of biological fluid, such as, for example, urine. Oneor more of the following techniques can be used to enhance thedetermination of the aforementioned parameter(s):

(1) using mathematical smoothing of spectra, e. g., polynomialsmoothing, to reduce noise in spectral measurements so that accuratecalibration and prediction are possible;

(2) computing a derivative of spectra before applying multivariateregression techniques to remove base-line drift in spectral measurementsand to bring the weaker spectral features that carry analyticalinformation into prominence;

(3) determining the major components of the biological system so thatthe residual fitting errors can be identified and removed by means of acalibration operation.

The following features can be used to enhance the determination of oneor more parameters of an analyte of interest in a sample of biologicalfluid, e g., urine:

(1) refractive index measurements and pH measurements can be combinedwith spectroscopic measurements, whereby detection of adulteration ofsamples intended for test of drugs of abuse or urinalysis can be carriedout;

(2) refractive index measurements, pH measurements, and use of reagentsfor analytes present in low concentration can be combined withspectroscopic measurements, whereby detection of adulteration of samplesintended for test of drugs of abuse or urinalysis can be carried out;

(3) impedance spectroscopy can be used to quantify analytes in a sampleof urine that have a unique impedance frequency signature.

Techniques for spectroscopic measurements and refractive indexmeasurements are well known to those of ordinary skill in the art. Bygathering and processing the data obtained in these measurements innovel ways, the accuracy of results can be improved. Techniques forspectroscopic measurements are described in Skoog and West, Principlesof Instrumental Analysis, Second Edition, Saunders College/Holt,Rinehart and Winston (Philadelphia:1980), pp. 113-351, incorporatedherein by reference. See also, B. Henderson, Handbook of Optics, 2ndedition, McGraw-Hill (New York:1995), chapter 20, incorporated herein byreference. Techniques for refractive index measurements are described inSkoog and West, Principles of Instrumental Analysis, Second Edition,Saunders College/Holt, Rinehart and Winston (Philadelphia:1980), pp.352-357, incorporated herein by reference. See also, E.

Hecht, Optics, 2nd edition, Addison-Wesley (Reading, Mass.:1988),pp.163-169, incorporated herein by reference. FIG. 1 illustrates asystem showing various types of measurements that can be carried outwith the method and apparatus of the present invention. The reagentlesssystem 10 comprises a sample handling subsystem 12, the purpose of whichis to introduce samples of biological fluid, e. g., urine, to theoptical measurement subsystems. The reagentless system 10 furthercomprises a refractive index determination subsystem 14, a visible lightspectroscopic subsystem 16, and an infrared light spectroscopicsubsystem 18. In the case of urinalysis, the refractive indexdetermination subsystem 14 can be used to determine the specific gravityof urine, the visible light spectroscopic subsystem 16 can be used todetermine color, turbidity, bilirubin, hemoglobin, urobilinogen, andprotein, or other analytes with a usable visible spectral signature, andthe infrared light spectroscopic subsystem 18 can be used to determineurea, creatinine, glucose, protein, and ketones, or other analytes thathave a usable near-infrared or mid-infrared spectral signature. Thereagentless system 10 may further comprise a subsystem 20 fordetermining pH and nitrites. The data obtained via the subsystems 14,16, 18, and 20 can be processed by means of data processing andcontrolling subsystem 22. The reagentless system 10 can be combined witha cell counter 24, the purpose of which is to determine leukocytes,bacteria, red blood cells, casts, crystals, and the like. Thereagentless system 10 can further be combined with a manual subsystem26, the purpose of which is to identify bacteria or further culturebacteria for drug resistance testing at a later time. FIG. 25 shows howspecific gravity can be determined from a determination of refractiveindex. FIG. 26 shows how pH determined by means of pH electrodescorrelates with pH determined by means of Bayer strips.

The sample handling subsystem 12 can comprise (1) a pump or equivalentmeans (a) (not shown) for aspirating a liquid sample into a sample cellassembly (not shown) for containing the sample during opticalmeasurements and to the pH determination subsystem 20 and (b) forremoving the liquid sample from the sample cell assembly and the pHdetermination subsystem 20 and delivering the removed sample to a wastecontainer (not shown), (2) an aspiration probe or other implement (notshown) for aspirating the sample, and (3) a flow control system (notshown), e. g., a three-way valve, so that the sample or a wash liquidmay be aspirated and dispensed through the sample handling subsystem 12.The liquid sample can be drawn into the sample cell assembly by means ofa pump or syringe mechanism (not shown). Alternatively, the liquidsample can be drawn into the sample cell assembly by means of a vacuum(not shown), such as a commercially available blood draw “VACUTAINER”tube. A filtering system 28 is preferably included to remove significantparticulate materials.

The refractive index determination subsystem 14 can comprise a source oflight (not shown) that generates a light beam, which is propagatedthrough a sample cell assembly (not shown). The refractive indexdetermination subsystem 14 can further comprise a detector (not shown)for detecting the deflection of the light beam that emerges from thesample cell assembly. The purpose of refractive index measurement is todetermine the percent solids in the liquid sample. The normal range ofthe refractive index can be defined by the technician, for examplebetween 1.336 and 1.345. The refractive index determination subsystem 14can be used to measure the percent solids dissolved in the liquidsample, as an indicator of degree of hydration of biological samples,particularly biological fluids, such as, for example, urine.

The visible light spectroscopic subsystem 16 can comprise a source ofvisible light (not shown). The source of visible light can be abroadband source, such as a tungsten filament lamp, if used inconjunction with a wavelength selection module (not shown).Alternatively, the source of visible light can be monochromatic orquasi-monochromatic, such as a laser diode or a light emitting diode.Multiple monochromatic light sources would be spatially or angularlymultiplexed by use of beam splitters, mirrors, and the like, such thatthe beams travel through substantially the same path through the samplecell assembly. The wavelength selection module can comprise a set offilters, a grating monochromator, a prism monochromator, anacousto-optic tunable filter, or any other wavelength dispersing device.The visible light spectroscopic subsystem 16 can comprise a detector(not shown) to determine the degree to which the light is affected bythe sample. The visible light spectroscopic subsystem 16 can be used todetermine color, turbidity, bilirubin, urobilinogen and hemoglobin, orother analytes with a usable visible spectral signature.

The infrared light spectroscopic subsystem 18 can comprise a source ofinfrared light (not shown). The source of infrared light can be abroadband source, such as a tungsten filament lamp, if used inconjunction with a wavelength selection module (not shown).Alternatively, the source of infrared light can be monochromatic orquasi-monochromatic, such as a laser diode or a light emitting diode.Multiple monochromatic light sources would be spatially or angularlymultiplexed by use of beam splitters, mirrors, and the like, such thatthe beams travel through substantially the same path through the samplecell assembly. The wavelength selection module can comprise a set offilters, a grating monochromator, a prism monochromator, anacousto-optic tunable filter, or any other wavelength dispersing device.The infrared light spectroscopic subsystem 18 can comprise a detector(not shown) to determine the degree to which the light is affected bythe sample. The infrared light spectroscopic subsystem 18 can be used todetermine urea, creatinine, glucose, protein, ketones, nitrites, orother analytes, with a usable near-infrared or mid-infrared spectralsignature. The purpose of a creatinine measurement, with respect to asample of urine, is to determine whether or not the creatinine level ofthe urine sample is within the normal range. The range that isconsidered to be normal can be defined by the technician, for example,above 20 mg/dL. If the creatinine level of the urine sample is below 20mg/dL the urine sample may be too dilute for accurate identification ofdrugs present in the urine. Dilution of a urine sample may have beencaused by excessive intake of water.

The pH determination subsystem 20 can comprise a standard pair ofelectrodes that measures a potential drop between a measurementelectrode and a reference electrode. The purpose of a pH measurement isto determine whether or not the pH level of a biological sample iswithin normal range. Normal range can be determined by the technicianand can range, for example, between 3 and 11. pH values outside of thisrange may indicate that materials have been added to the biologicalsample for the purpose of producing a false negative in a drugs of abusedetermination. Alternatively, pH outside this range may indicate thatmaterials may have been added to the biological sample to alter ordestroy enzymes.

Nitrites (NO₂) can be measured by means of spectroscopy, by means of ionselective electrodes, or by adding a reagent and making a calorimetricmeasurement. The purpose of a NO₂ measurement, with respect to a sampleof urine, is to determine if NO₂ has been added to the sample of urinefor the purpose of producing a false negative test result for a drug ofabuse in a drug of abuse adulteration test. Determination of NO₂ canalso be used as an indicator for an infection in a urinalysis test.

A colorimetric measurement subsystem that utilizes one or more reagentsmay be included as needed to measure the concentration of an analyte ofinterest in a biological sample, either when the concentration of theanalyte is too low to allow measurement by spectroscopy, or when thespectral signature of the analyte is insufficient to allow accuratemeasurement of the concentration. An impedance spectrometric measurementdevice may be included to measure the impedance of the biological sampleat one or more frequencies for the purpose of measuring theconcentration of an analyte of interest that cannot be measured byabsorption spectroscopic analysis but that has a unique impedancespectral signature.

The data processing and controlling subsystem 22 contains a detector(not shown) to measure how the light is affected by the sample in thesample cell assembly, an amplifier (not shown) to amplify the signalfrom the detector, and an A/D (analog to digital) converter (not shown)to convert the amplified signal to a number, and a signal processor (notshown) to process the data. A reference detector (not shown) determinesa signal proportional to the power of the source incident on the samplecell assembly. This signal may be used to compensate for sourcefluctuations in software, or to actively adjust the power to the sourceto stabilize its output. The aforementioned reference detector may beeliminated if the source of light is sufficiently stable to obtainaccurate results.

Additional features that can be combined with the foregoing subsystemsinclude a cell-counting subsystem. When positive values are obtained forleukocytes or nitrites or blood in a sample of urine, a more detailedmicroscopic evaluation of urine sediment is called for. To obtain aurine sediment determination, a sample of urine is centrifuged to formpellets of sediment materials in urine. The sediment materials includeleukocytes, red blood cells, cell ghosts, bacteria, crystals, and casts.The sediment pellet is transferred to a slide and a skilled technicianmust quantify the material by inspection. Such a process istime-consuming and costly.

Recent literature (Y. Yasui et al., “Urinary Sediment Analyzed by FlowCytometry”, Cytometry 22(1):75-79, 1995) suggests that the formedelements may be quantified by cell counting methods, which employ lightscattering and/or urine impedance measurements. A system that combinescell counting technology with one or more of spectroscopic measurements,refractive index measurements, pH measurements, and ion selectiveelectrodes could bring about complete automation of urinalysis, therebysaving time for a trained technician and saving cost for the testinginstitution.

Another feature that can be combined with the foregoing subsystems is amanual subsystem, which typically includes microscopy. Microscopy ofurine sediment allows a trained, experienced technician to identify anumber of disease indicators in urine, such as, for example, red cells,white cells, bacteria, casts, and crystals. Microscopy, as it iscurrently practiced in many laboratories, is a manual, time-consumingprocess involving a number of steps. To begin the process, urine must becentrifuged for five minutes at about 80×g, causing formed elements topellet at the bottom of the centrifuge tube. Most of the supernatanturine is carefully decanted, leaving only a small amount of urine tore-suspend the pellet. After re-suspension, the re-suspended pellet isspread on a microscope slide, and examined first under low and laterunder high power magnification to search for red cells, leukocytes,bacteria, casts, and crystals. Subdued lighting helps identify hyalinecasts and crystals that are nearly transparent in bright fieldmicroscopy. With increased lighting, fat bodies change from dark tolight and become highly refractile in bright field microscopy. Withpolarized light, fat bodies become especially visible as they typicallycontain significant quantities of cholesterol, a refractile material.The structure of urine casts may indicate their origin, and a trainedeye is needed to accurately identify structures. In a separate step,addition of biological stains to the urine sediment enhances thetechnologist's ability to identify red cells, leukocytes and bacteria inurine. See Clinical Chemistry: Theory, Analysis, and Correlation, secondedition, Kaplan, L. A. and Pesce, A. J. (Editors), (C.V. MosbyCompany:1989), pages 832-848, incorporated herein by reference.

In a preferred embodiment, as shown in FIGS. 2, 3, 4, 5, and 6, theapparatus 100 comprises a spectral measurement assembly 102, arefractive index determination assembly 104, a pH electrode assembly106, and a fluid pump assembly 108.

The purpose of the spectral measurement assembly is to utilize spectralmeasurements to determine the concentration of at least one analyte ofinterest in a biological sample, more particularly a biological fluid.

The spectral measurement assembly 102, shown in detail in FIG. 3,comprises a source of light 110, a scanning monochromator 112, acollimating lens (not shown), a holder 116 for the collimating lens, alens holder/beam splitter assembly 118, a focusing lens (not shown), abeam splitter 120, a reference detector 122, a sample cell assembly 124,and an absorption detector 126. The functions of the foregoingcomponents are well known to those of ordinary skill in the art.However, the functions will be briefly described in the context of thepresent invention. The source of light 110 provides the light for thespectral measurement. The monochromator 112 selects the wavelength foran absorption measurement. The collimating lens collimates the beam oflight emerging from the scanning monochromator 112. The holder 116supports the collimating lens. The lens holder/beam splitter assembly118 holds the focusing lens and the beam splitter 120. The beam splitter120 diverts a portion of the light entering the assembly 118 to thereference detector 122, which indicates the intensity of the source oflight 110. This is particularly important in order to compensate for thedrift of the source of light. Light source fluctuation could result frompower variation, temperature variation, and age of the source of light.The sample cell assembly 124 has a chamber that contains the biologicalsample undergoing the spectroscopic measurements. The focusing lensfocuses the collimated light onto the biological sample in the samplecell assembly 124. The absorption detector 126 measures the quantity oflight absorbed by the biological sample. Not shown are the electroniccomponents for processing data and controlling the functional componentsof the apparatus.

When a scanning monochromator is used in the arrangement shown in FIG.3, the wavelength of the light is selected before the beam of light ispropagated through the sample. In some circumstances it is preferred touse an array spectrometer in place of the scanning monochromator. Whenarray spectrometer is used, the beam of light from the source of lightenters the sample. The beam of light exiting the sample is then focusedonto the entrance aperture of the array spectrometer. The light withinthe beam is then dispersed onto a detector array, such that the detectorarray measures the intensity of the beam as a function of wavelength.The advantage of a detector array is that it provides the capability ofmeasuring the spectra very quickly, typically less than one second.Array spectrometers are described in detail in B. Henderson, Handbook ofOptics, 2nd edition, McGraw-Hill (New York:1995), chapter 20,incorporated herein by reference. A commercially available scanningmonochromator is a TR190MS2 monochromator from Instruments SA. Acommercially available array spectrometer is a NIROSC array spectrometerfrom Control Development. It should be noted that a monochromatordiffers from a spectrometer in that a spectrometer includes a detectorand a monochromator does not include a detector.

An alternative to the spectral measurement assembly 102 can be a filterphotometer assembly 202, shown generally in FIG. 4 and in detail in FIG.5. In FIG. 4, the remaining components of apparatus 100, namely, therefractive index determination assembly 104, the pH electrode assembly106, and the fluid pump assembly 108 remain unchanged. Turning to FIG.5, the filter photometer assembly 202 comprises a stepping motor 204, asource of light 206, a light source modulator 208, a collimating lens210, a holder 212 for the collimating lens 210, a filter cartridge 214,selected filters 216, a lens holder/beam splitter assembly 218, afocusing lens (not shown), a beam splitter 220, a reference detector222, a sample cell assembly 224, and an absorption detector 226. Thefunctions of the foregoing components are well known to those ofordinary skill in the art. However, the functions will be brieflydescribed in the context of the present invention. The source of light206 provides the light for the spectral measurement. The light sourcemodulator 208 modulates the amplitude of the beam from the source oflight to allow phase-locked detection, which provides better rejectionof noise. The collimating lens 210 collimates the beam of light emergingfrom the source of light 206. The holder 212 supports the collimatinglens 210. The filters 216 select the appropriate wavelength for ameasurement of absorption of a sample. The filter cartridge 214 containsthe filters 216. The stepping motor 204 moves the filter cartridge 214so that the appropriate filter 216 will be in the path of the beam oflight emerging from the collimating lens 210. The lens holder/beamsplitter assembly 218 holds the focusing lens and the beam splitter 220.The beam splitter 220 diverts a portion of the light entering theassembly 218 to the reference detector 222, which, as stated previously,indicates the intensity of the source of light 206. This is particularlyimportant in order to compensate for the drift of the source of light.Light source fluctuation could result from power variation, temperaturevariation, and age of the source of light. The sample cell assembly 224has a chamber that contains the biological sample undergoing thespectroscopic measurements. The focusing lens focuses the collimatedlight onto the biological sample in the chamber of the sample cellassembly 224. The absorption detector 226 measures the quantity of lightabsorbed by the biological sample. Not shown are the electroniccomponents for processing data and controlling the functional componentsof the apparatus.

The refractive index determination assembly 104, shown in detail in FIG.6, comprises a sleeve 302, a source of light 304, such, for example, alaser diode emitter, a mount 306 for the sleeve 302 and the source oflight 304, a lens 308, a translational mount 310 for the source of light304, a sample cell assembly 312, a detector 314, such as, for example, aposition-sensitive detector, and a mount 316 for the detector 314. Thefunctions of the foregoing components are well known to those ofordinary skill in the art. However, the functions will be brieflydescribed in the context of the present invention

A preferred source of light for the refractive index determination is alaser.

Lasers are preferred to other sources of light, such as a conventionallamp, because it is an inexpensive way to provide monochromic light,which results in better sensitivity on measuring light bending byrefractive index of sample. In FIG. 6, the source of light 304 is alaser diode emitter. The sleeve 302 and the translational mount 310function to properly align the beam from the source of light 304. Thelens 308 focuses the light from the source of light 304 onto the samplecell assembly 312, which has a chamber that contains the biologicalsample. The detector 314 measures the change of position of the beam oflight from the source of light 304 brought about by the biologicalsample. The pH electrode assembly 106 can be described in a mannersimilar to that of the pH determination subsystem 20, which waspreviously described. The fluid pump assembly 108 can be described in amanner similar to that of the sampling handling subsystem 12, which waspreviously described.

All of the components shown in FIGS. 2, 3, 4, 5, and 6, with theexception of the sample cell assembly, are commercially available, andthe apparatus in these figures can be readily assembled by one ofordinary skill in the art. It should also be noted that although samplecell assemblies 124, 224, and 312 have different reference numerals,they are intended to be identical in FIGS. 3, 5, and 6.

The sample cell assembly of this invention allows both spectroscopicmeasurements and refractive index measurements to be made with the samesample at substantially the same time. The sample cell assembly 400,shown in detail in FIGS. 7, 8, and 9A, comprises a body 402, a cover 404for the body 402, a sample inlet tube 406, a sample outlet tube 408, aspectroscopic measurement entrance window 410 and a spectroscopicmeasurement exit window 412, and a refractive index measurement entrancewindow 414 and a refractive index measurement exit window 416. Thewindow 410 into which the beam for conducting spectroscopic measurementsenters the sample cell assembly 400 and the window 412 from which thebeam for conducting spectroscopic measurements exits the sample cellassembly 400 are parallel to one another. The window 414 into which thebeam for conducting refractive index measurements enters the sample cellassembly 414 and the window 416 from which the beam for conductingrefractive index measurements exits the sample cell assembly 400 are notparallel to one another. The body 402, the cover 404, the windows 410,412, 414, and 416 form the boundaries of a chamber that contains thebiological sample. As shown in FIG. 7, the beam for spectroscopicmeasurements B_(s) and the beam for measuring refractive index B_(ri)are propagated through the sample cell assembly 400 such that the beamfor spectroscopic measurements does not interfere with the beam formeasuring refractive index and vice versa.

The interior of the sample cell assembly 400, i. e., the chamber thatcontains the biological sample, is divided into three zones: (1) anexpansion zone 418, (2) a read zone 420, and (3) a contraction zone 422.In the expansion zone 418, the flow front of the sample expands. Theexpansion zone 418 is designed such that the amount of surface area incontact with the fluid is minimized to reduce the likelihood of bubbleformation caused by fluid clinging to the interior surfaces of thesample cell assembly and to minimize cleaning requirements of theinterior surfaces of the sample cell assembly. The expansion zone 418 isalso designed to eliminate regions where fluid may become trapped,thereby resulting in difficulties in washing the interior surfaces ofthe sample cell assembly for subsequent samples. In the contraction zone422, the flow front of the sample contracts. Like the expansion zone418, the contraction zone 422 is also designed such that the amount ofsurface area in contact with the fluid is minimized to reduce thelikelihood of bubble formation caused by fluid clinging to the interiorsurfaces of the sample cell assembly and to minimize cleaningrequirements of the interior surfaces of the sample cell assembly. Theread zone 420 for absorption measurements should be large enough toallow the absorption beam to pass through the entrance window and theexit window without being substantially truncated. The read zone 420 forrefractive index measurements should be large enough to allow therefractive index beam to pass through the entrance window and the exitwindow without being substantially truncated. The read zones for theabsorption measurements and the refractive index measurements maycoincide or they may not, depending on system design considerations. Theread zones 420 for the absorption measurements and refractive indexmeasurements in FIGS. 7, 8, and 9A are shown to coincide, therebyreducing required sample volume.

In the sample cell assembly 400 shown in FIGS. 7, 8, and 9A, the sampleflows into the inlet tube 406 and through the contraction zone 422 tothe read zone 420, where it resides during the time needed for opticalreadings. After the optical readings are taken, the sample flows fromthe read zone 420 through the contraction zone 422, and is then removedfrom the sample cell assembly 400 by means of flowing through the outlettube 408. In an alternative embodiment, shown in FIG. 9B, the sampleenters and exits the sample cell assembly by way of the inlet tube 406′.The sample cell assembly of the alternative embodiment does not have anoutlet tube distinct from the inlet tube 406′. In the alternativeembodiment, the sample flows into the inlet tube 406′ and through theexpansion zone 418′ to the read zone 420′, where it resides during thetime needed for optical readings. After the optical readings are taken,the sample flows from the read zone 420′ back though the expansion zone418′, and is then removed from the sample cell assembly by means offlowing back through the inlet tube 406′. In the alternative embodiment,the expansion zone 418′ serves as the contraction zone when the sampleis removed from the sample cell assembly.

The sample cell assembly of this invention can be used to simultaneouslymeasure refractive index and ultraviolet, visible, or infrared spectrum.While not preferred, it is acceptable to replace the sample cellassembly of this invention with two or more sample cell assemblies intandem for separate measurements.

Materials for forming the windows of the sample cell assembly are wellknown to those of ordinary skill in the art. However, parameters of themost critical materials of the sample cell assembly will now bedescribed to clearly set forth the important features of the sample cellassembly. Spectroscopic measurement windows 410 and 412 are preferablyformed from glass or fused silica, and refractive index measurementwindows 414 and 416 are preferably formed of glass, fused silica, orpolymeric materials. The distance between the spectroscopic measurementwindows 410 and 412 preferably ranges from about 100 μm to about 5 cm,more preferably 1 mm. The angle between the refractive index measurementwindows 414 and 416 preferably ranges from about 5° to about 60°, morepreferably 30°. Wavelengths of light suitable for refractive indexmeasurement preferably ranges from about 500 nm to about 1000 nm.Wavelengths of light suitable for spectroscopic measurement preferablyranges from about 300 nm to about 2500 nm. The volume of the interior ofthe sample cell assembly, i. e., the chamber that contains thebiological sample, is not critical; however, it is preferred that thevolume of the interior of the sample cell assembly be of sufficient sizeso that it can contain a sufficient volume of sample for the desiredoptical measurements.

The method of this invention differs from that disclosed in U.S. Pat.No. 5,696,580, which proposes measuring absorbance and refractive indexthrough a sample cell assembly having at least one face of the samplecell assembly tilted with respect to the axis along which the beam usedfor absorption propagates. In U.S. Pat. No. 5,696,580, the beam ofinfrared light and the beam of light for measuring refractive indextravel in the same direction through the sample cell assembly. Thiscommon path for the two beams leads to two significant problems.

First, a sample cell assembly having a triangular shape (as described inU.S. Pat. No. 5,696,580) makes implementation of an array spectrometerdifficult. An array spectrometer must be used for measurements ofanalytes in urine in order to increase the speed of analysis. In anarray spectrometer, the light rays are fanned out as a function ofwavelength. The fanned out light rays are projected onto an arraydetector such that each detector element of the array detector observesa different wavelength. If the fanned out light rays are firsttransmitted through the triangular-shaped sample cell assembly, then thedetector element that each light ray strikes will change as therefractive index of the urine sample changes. Compensation for thiseffect is complicated, requires excessive computation, and willintroduce its own sources of noise.

Second, if an array spectrometer cannot be employed, a scanningspectrometer must be used. Measurement of the refractive index andabsorption in a scanning spectrometer would require a split aperturedetector. A split aperture detector is one in which the detector areacomprises two independent detectors that are joined in the center.Calibration is problematic if there is a gap, which is referred to as adead zone, between the detectors. A dead zone is an area in which thedevice does not respond to the light. Practically, a dead zone cannot beavoided because the two detectors cannot be butted together perfectly.The larger the dead zone, the more problematic the calibration. Thereason for the difficulty in calibration is that the beam does not havea uniform intensity distribution when it is projected onto the detector.If the beam is translated slightly, a different part of the beam strikesthe dead zone. If the intensity of the beam is not uniform, then themeasured intensity will change as the beam moves across the dead zone.Because the beam is intended to move across the split aperture detector,the presence of the dead zone will be a source of error. The larger thedead zone, the larger the error.

In the method of this invention, the beam for refractive indexmeasurements and the beam for spectroscopic measurements are notco-linear. The absorption measuring beam passes through a sample cellassembly having plane parallel windows. Thus, scanning spectrometers andarray spectrometers can both be employed in the usual way withestablished performances.

The method of this invention preferably employs a position-sensitivedetector that works in the visible spectrum and is designed to eliminatea dead zone —it is not a split aperture detector.

Mathematical assumptions and relationships that are essential to theunderstanding of the operation of this invention will now be described.

FIG. 10 illustrates an arrangement for determining the refractive indexof a biological fluid, wherein the sample-containing chamber of thesample cell assembly of this invention is in the form of a prism. In thearrangement 500 for determining refractive index of a sample ofbiological fluid, a source of light 502 provides a beam of light, whichis collimated by a lens 504. The beam of collimated light enters thechamber 506 of the sample cell assembly. The beam of light for measuringrefractive index is incident on a window 508 of the chamber 506 of thesample cell assembly at an angle of θ₁ degrees; the beam refracts intothe chamber 506 of the sample cell assembly and then into the sample“U”. The relationship between the incident angle and the angle of thebeam inside the chamber 506 of the sample cell assembly is given by

n ₀ sin(θ₁)=n _(s) sin(θ₂)  (1)

where

n₀ represents the refractive index of air (1.000) and

n_(s) represents the refractive index of the sample.

This relationship is independent of the refractive index of the materialof the entrance window 508 of the chamber 506 of the sample cellassembly. The relationship between the incident angle of the beam at anexit window 510 of the chamber 506 of the sample cell assembly (θ₃) andthe angle of the beam outside the sample cell assembly (θ₄) is given by

n _(s) sin(θ₃)=n ₀ sin(θ₄)  (2)

Solving for θ₄ in terms of the refractive index of the sample and theincident angle θ₁, $\begin{matrix}{\theta_{4} = {\sin^{- 1}\left\lbrack {n_{s}\sin \quad \left( {\alpha - {\sin^{- 1}\left\lbrack \frac{\sin \quad \left( \theta_{1} \right)}{n_{s}} \right\rbrack}}\quad \right)} \right\rbrack}} & (3)\end{matrix}$

where α=θ₂+θ₃.

For small changes in refractive index, equation (3) becomes a linearfunction of the refractive index

 θ₄ =An _(s) +B  (4)

where A and B are constants. The displacement on the detector 512 isgiven by

D=A′n _(s) +B′  (5)

where

A′ and B′ are constants that are determined in a calibration step, and

D represents the displacement on the detector.

A two-point calibration can be used to determine the two unknownconstants. The first calibration point could be done with water(refractive index n=1.333) and the second calibration point could bemade with a solution having a refractive index of 1.450. These twomeasurements would determine the relationship between L and therefractive index (slope and intercept) that can be used to determinesubsequent refractive indices of solutions from the measured beamdisplacements. Additional calibration solutions can be measured so thata least squares fit can be used to determine the two unknown constants.

FIG. 11 illustrates an arrangement for determining the refractive indexof a biological fluid, wherein at least one window of thesample-containing chamber of the sample cell assembly of this inventionis curved. In the refractive index determination arrangement 600 shownin FIG. 11, a source of light 602 transmits a beam of light through acollimating lens 604. The beam of collimated light emerging from thelens 604 enters the chamber 606 of the sample cell assembly. The beam oflight emerging from the chamber 606 of the sample cell assembly isdetected by a detector 608, preferably a detector having a plurality ofdetection elements. In the chamber 606 of the sample cell assembly, atleast one window of the chamber 606 of the sample cell assembly iscurved so that the chamber 606 of the sample cell assembly no longeroperates in the manner of a prism, but rather operates in the manner ofa lens. As shown in FIG. 11, an entrance window 610 of the chamber 606of the sample cell assembly is curved and an exit window 612 isstraight. However, the exit window 612 can also be curved, or theentrance window 610 can be straight and the exit window 612 can becurved. As the refractive index of the biological sample changes, thepower of the “lens” formed by the chamber 606 of the sample cellassembly also changes. Consequently, the point, i. e., the focal point,to which the “lens” formed by the chamber 606 of the sample cellassembly focuses the beam of light emerging from the sample cellassembly also changes. The detector 608 is in a fixed position relativeto the “lens” formed by the chamber 606 of the sample cell assembly.This position is near the focal point “P” of the “lens” formed by thechamber 606 of the sample cell assembly. The focal point “P” is thefocal point when the sample in the chamber 606 of the sample cellassembly is water. The size of the spot of the beam of light strikingthe detector 608 will change as the focal point “P” changes. The size ofthe spot of the beam of light striking the detector 608 is proportionalto the refractive index of the biological sample, i. e., as therefractive index of the biological sample changes, the size of the spotof the beam of light striking the detector 608 changes. The shape of thechamber 606 of the sample cell assembly is not preferred over a chamberof a sample cell assembly having a prism configuration, because theformer is more sensitive to scattering from particulate material in thebiological sample, but it would be expected to be suitable for manyapplications.

FIG. 12 illustrates an arrangement 700 for use in determining therefractive index of a biological fluid comprising a sample-containingchamber 702 of a sample cell assembly, wherein an entrance window 704 ofthe chamber 702 of the sample cell assembly is parallel to an exitwindow 706 of the chamber 702 of the sample cell assembly. Although notshown in FIG. 12, this arrangement also employs components than generateand collimate a beam of light, equivalent to that shown in FIG. 11.

The entrance window 704 and the exit window 706 are parallel to oneanother. A detector 708, preferably a position-sensitive detector, ispositioned substantially adjacent to the exit window 706 of the chamber702 of the sample cell assembly to receive the refracted beam of light.As used herein, the expression “substantially adjacent” includes both incontact with and at a small separation. The beam of light fordetermining the refractive index is incident on a first surface of theentrance window 704 at an angle θ₁, which is greater than zero.Preferably, this angle ranges from about 45° to about 85°. Lesspreferably, this angle can range from about 5° to about 45°. Thedistance between the entrance window 704 and the exit window 706preferably exceeds 5 mm, but can be less. The equation relatingrefractive index to the position of the beam on the detector is$\begin{matrix}{d = {\frac{L}{n}\sin \quad \left( \theta_{1} \right)}} & (6)\end{matrix}$

where

L represents the distance between the entrance window and the exitwindow,

n represents the refractive index of the sample inside thesample-containing chamber of the sample cell assembly, and

d represents the vertical distance between the position at which thebeam of light enters the sample-containing chamber of the sample cellassembly and exits the sample-containing chamber of the sample cellassembly.

The methods of spectroscopic analysis of this invention are not limitedto absorption spectroscopy. All methods of spectroscopic analysis arecontemplated for use with this invention, and, in particular, thosespectroscopic analysis techniques set forth in Skoog and West,Principles of Instrumental Analysis, Second Edition, SaundersCollege/Holt, Rinehart and Winston (Philadelphia:1980), pp. 113-351,incorporated herein by reference and B. Henderson, Handbook of Optics,2nd edition, McGraw-Hill (New York:1995), chapter 20, incorporatedherein by reference. These spectroscopic analysis techniques include,but are not limited to, ultraviolet spectroscopy, including ultravioletscattering spectroscopy, visible spectroscopy, including visiblescattering spectroscopy, infrared spectroscopy, including infraredscattering spectroscopy, fluorescence spectroscopy, and Ramanspectroscopy. Also included is spectroscopic analysis utilizingmeasurement of transmitted light and spectroscopic analysis utilizingmeasurement of reflected light. Common practices in spectroscopy aredetection of transmitted light to measure light intensity after aportion of the light is absorbed by a clear liquid sample and detectionof reflected light to measure light intensity after a portion of thelight is absorbed or scattered by a turbid liquid or a solid sample.Scattering spectroscopy may be defined as measuring (a) the attenuationof light caused by propagation of light through a medium that is capableof absorbing and scattering light, or (b) the attenuation of lightcaused by specular and diffuse reflection of light from an absorptivesample.

The method and apparatus of this invention not only removes base-linedrift from the measured spectra, but also prominently displays spectralfeatures unique to the analytes of interest. Removal of base-line drift,separation of spectral features, and noise reduction are necessary forspectroscopic analysis to provide accurate results. Derivativespectroscopy is a technique that can be used to bring about noisereduction. Derivative spectrophotometry is defined in Skoog and West,Principles of Instrumental Analysis, Second Edition, SaundersCollege/Holt, Rinehart and Winston (Philadelphia:1980), pp. 192-194,incorporated herein by reference. See also, B. Henderson, Handbook ofOptics, 2nd edition, McGraw-Hill (New York:1995), chapter 20,incorporated herein by reference. Derivative spectroscopy, as usedherein, will now be described.

The spectrum of urine comprises the spectrum of water plus the spectraof urea, creatinine, glucose, ketones, and many other chemicalsubstances dissolved in the urine. The calibration process describedherein can determine a mathematical operator (i. e., a model) that willsimultaneously convert the absorption spectrum of a urine specimen intothe concentration values of chemical components of interest in the urinespecimen.

Beer's Law relates the absorbance of a chemical substance (a), theconcentration of the substance (c), and the path length of the light (L)to the ratio of intensity of incident light (I_(o)) to intensity oftransmitted light (I), $\begin{matrix}{\frac{I}{I_{0}} = e^{- {Lca}}} & (7) \\{s_{q,1} = {{{- \log}\quad \left( \frac{I_{q}}{I_{0,q}} \right)} = {{Lc}_{n}a_{q,n}}}} & (8)\end{matrix}$

where

s_(q,n) represents the q^(th) element (wavelength) of the n^(th) analyteof the sample,

L represents the path length of the light,

c_(n) represents the concentration of the n^(th) analyte in the sample,and

a_(q,n) represents the q^(th) element of the spectrum for the n^(th)analyte,

I_(o,q) represents the intensity of the incident light for the q^(th)wavelength,

I_(q) represents the intensity of the transmitted light for the q^(th)wavelength.

The absorption spectrum S for urine can be expressed by the equation

S=L[c _(w) a _(w) +c ₁ a ₁ +c ₂ a ₂ . . . +c _(n) a _(n) . . . +c _(N) a_(N)]  (9)

where

c_(w)a_(w) represents the product of the concentration of water andspectrum of water,

c_(n)a_(n) represents the product of the concentration of the n^(th)analyte and absorption of the n^(th) analyte,

c_(N)a_(N) represents the product of the concentration of the N^(th)(final)analyte and spectrum of the N^(th) (final) analyte, and

L is as previously defined.

The spectrum of an aqueous liquid, e. g., urine, for the ideal case doesnot consider noise and base-line drift, which are integral parts of themeasurement process. The measured spectra of aqueous liquids are oftenunsuitable for analytical treatment. FIG. 13 shows the absorptionspectrum of water and the absorption spectrum of urine. The solid blackline is the absorption spectrum of water and the dotted black line isthe absorption spectrum of urine. In order to clearly feature thespectrum of an analyte of interest, e. g., urea, the water backgroundmust be subtracted from the spectrum of the aqueous solution containingthe analyte of interest, e. g., urine. Because each point on eachspectrum is a large number, and because one large number must besubtracted from another large number to observe a small difference, bothof the spectra must be determined very precisely. Because practicalconsiderations, such as noise, limit the precision of the spectralmeasurements, methods must be developed to deal with the noise in orderto make spectroscopy useful for accurately recovering the concentrationvalues of analytes in an aqueous solution, e. g., urine.

As a first step, base-line drift must be removed from the data. Abase-line drift as low as 1% can cause large errors in the determinationof the concentration of an analyte. By taking a first derivative of thespectrum of a biological sample, changes in the base-line signal can beremoved. The derivative provides two features. First, it removes thebase-line drift from the measured spectrum, and second, it brings toprominence the weaker features in the spectrum that carry analyticalinformation.

In the presence of base-line drift, equation (8) becomes $\begin{matrix}{s_{q,n} = {{{- \log}\quad \left( \frac{I_{q,n}}{\left( {I_{0,q,n} + {\Delta \quad I_{0,q,n}}} \right)} \right)} = {{{- {\log \quad\left\lbrack \frac{I_{q,n}}{I_{0,q,n}} \right\rbrack}} + \left\lbrack \frac{\Delta \quad I_{0,q,n}}{I_{0,q,n}} \right\rbrack + {\frac{1}{2}\quad\left\lbrack \frac{\Delta \quad I_{0,q,n}}{I_{0,q,n}} \right\rbrack}^{2} + \ldots} = {{{Lc}_{q}a_{q,n}} + \left\lbrack \frac{\Delta \quad I_{0,q,n}}{I_{0,q,n}} \right\rbrack + {\frac{1}{2}\quad\left\lbrack \frac{\Delta \quad I_{0,q,n}}{I_{0,q,n}} \right\rbrack}^{2} + \ldots}}}} & (10)\end{matrix}$

where

I_(q,n) represents the intensity of light transmitted by the sample atthe q^(th) wavelength,

I_(0,q,n) represents the intensity of light incident on the sample atthe q^(th) wavelength, and

ΔI_(0,q,n) represents the drift in the intensity of incident light atthe q^(th) wavelength.

The above expression (10) can be generalized for other sources of drift,such as, for example, detector drift and electronics drift. Most sourcesof drift, including source, detector, and electronics drift, aresufficiently spectrally flat, i. e., lacking in spectral features suchas peaks and valleys, that taking the derivative is helpful in removingthe drift.

To first order approximation, which is a good approximation for smallamounts of drift, $\begin{matrix}{s_{q} = {{Lca}_{q} + \left\lbrack \frac{\Delta \quad I_{0,q}}{I_{0,q}} \right\rbrack}} & (11)\end{matrix}$

If the base-line drift on the spectrometer is spectrally flat, which istypically the case, then the dependence of the drift on wavelength issmall, and the derivative of the drift with respect to wavelength isvery small. To a very good approximation $\begin{matrix}{\frac{s_{q}}{\lambda} = {{Lc}\frac{a_{q}}{\lambda}}} & (12)\end{matrix}$

Thus, the drift can be eliminated from the measurement.

FIGS. 14 through 23 illustrate the second advantage to carrying outderivative spectroscopy. FIG. 14 shows the spectra of urea, creatinine,glucose, albumin, ketones, and nitrites after the absorption spectrum ofwater c_(w)a_(w) has been subtracted. FIG. 14 was prepared by creatingaqueous solutions of the above-mentioned analytes in water. Theconcentrations of the above-mentioned analytes are much greater thanwhat would be expected in actual samples of urine, and theconcentrations are shown at large values so that the spectral structureof these analytes can be observed. FIGS. 15 through 19 show thederivative spectra of the same six analytes individually or incombination for better comparison. FIG. 15 shows the derivative spectraof urea, creatinine, and glucose. FIG. 16 shows the derivative spectraof albumin, nitrites, and ketones. FIG. 17 shows the spectrum of urea ata concentration of 200 mg/dL. FIG. 18 shows the spectrum of glucose at aconcentration of 100 mg/dL. FIG. 19 shows the spectrum of albumin at aconcentration of 50 mg/dL. The second advantage of using the derivativespectroscopy is that the differences in the spectral structures betweenthe analytes becomes more pronounced. As more unique features can bebrought out of the spectral structure, the more specific the measurementof concentration of an analyte can be.

In FIGS. 15 through 19, the concentrations of the analytes weresufficiently high and the magnitudes of the spectra sufficiently greatthat the noise extraneous to the signal was significantly smaller thanthe level of the signal. In clinical situations, however, the noiselevel for typical concentrations of these analytes is much largerrelative to the signal strength. FIGS. 17 through 19 show spectra takenof urea, glucose, and albumin, respectively. These spectra were obtainedusing a state-of-the-art FTIR spectrometer optimized for measurementsmade in this wavelength range. Each figure shows the derivative spectrumand the smoothed derivative spectrum. FIG. 20 shows a typical spectrumof the noise that is removed from the derivative spectra with apolynomial noise reduction filter. That this noise spectrum is randomcan be established by visual inspection of the spectrum. Because (1) themagnitude is relatively small, (2) the values are distributed equallyabove and below zero, and (3) the average of the values approach zero,it can be assumed that the noise spectrum is random. There are othermore sophisticated methods to ensure that the removed noise is randomnoise. One such method involves calculating the auto-correlationfunction. A single high peak at the origin of the auto-correlationfunction suggests that the noise is random noise.

The purpose of a noise reduction filter is to reduce the random noisesuperposed on the spectrum without distorting the spectral featuresassociated with the analytes. A useful technique for this purpose is touse a mathematical function that would represent the spectral featureswhile differentiating the random noise from the spectral features. Thereare several mathematical functions that can be used for this purpose.For example, a polynomial function, a Taylor series function, a Fourierseries function, or a Gaussian function could approximate slowly varyingspectral features. The random nature of the noise removed from thespectra in FIGS. 17 through 19 provides evidence that the features ofthe spectra have not been distorted. It has been discovered that thespectral features associated with the analytes can be approximated verywell by a low order polynomial (e. g., a quadratic equation) over asmall wavelength range. Preferably, the wavelength range has a width offrom 1 nm to about 100 nm. In addition, the orders of the polynomialfunctions employed can be varied from spectral region to spectral regionacross the spectrum. The aforementioned spectral features can very oftenbe represented by a quadratic equation. In other words, the spectralfeatures associated with the analytes of interest in the infrared regionhave the form of a low order polynomial function,

a=x ₀ +x ₁ λ+x ₂λ²  (13)

where

a represents absorption,

x_(n) where, n=0, 1, 2, are the coefficients, and

λ represents the wavelength.

It has been discovered that this equation provides an optimal fit forthe infrared spectral region and that low order polynomials provide asuitable approximation of the underlying spectral feature that is to beobserved.

The noise reduction method contemplated herein for the spectrum of abiological sample can be described by the following steps:

(a) identifying a mathematical function that is substantially similar toa region of a non-smoothed spectrum of the sample over a selected rangeof the non-smoothed spectrum;

(b) selecting a portion of the region of the non-smoothed spectrum suchthat noise in the selected portion is substantially random;

(c) determining coefficients of the mathematical function that result ina close fit of the function to the selected portion of the non-smoothedspectrum;

(d) calculating at least one value of the non-smoothed spectrum at atleast one wavelength of the non-smoothed spectrum by means of thecoefficients and the mathematical function of step (c), wherein said atleast one wavelength includes the center of the region of thenon-smoothed spectrum;

(e) assigning said at least one calculated value of the non-smoothedspectrum to a wavelength including the center of the selected portion ofthe region of the non-smoothed spectrum to form at least one point of asmoothed spectrum;

(f) shifting a selected distance in the non-smoothed spectrum andrepeating steps (c), (d), and (e) until a desired amount of the smoothedspectrum is formed;

(g) forming a residual spectrum by subtracting each point of the desiredamount of the smoothed spectrum at a given wavelength from each point ofthe non-smoothed spectrum at said given wavelength;

(h) inspecting the residual spectrum to determine if it is random; and

(i) if the residual spectrum is not random, repeating steps (b), (c),(d), (e), (f), (g), and (h) to achieve a smoothing, wherein saidresidual spectrum is random.

In the foregoing method, the expression “close fit” means having littleor no space between the measured spectrum and the selected mathematicalfunction at a given wavelength. However, the closeness of fit is withinthe discretion of the user of the method and is not critical in thecarrying out of the method of this invention. For example, the user canrequire that the fit of the selected mathematical function at any givenwavelength be within 1%, 2%, 3%, 5%, 7%, 10%, or greater, of themeasured value of the spectrum at that wavelength. The experience of theuser, the requirements of the measurement, and the limitations of thecomputer are factors that should be considered in the selection of thecloseness of fit. The expression “desired amount” is also within thediscretion of the user of the method and is not critical in the carryingout of the method of this invention. For example, the user can requirethat the desired amount of the smoothed spectrum encompass a range basedon the spectral feature of the analyte of interest and the conveniencein carrying the computing steps. For example, in urinalysis, the desiredamount could be the central 50% to 80% of the spectral range during theinitial iteration of steps taken while searching for the optimal size ofthe spectral region for fitting. The desired amount could be the central90% to 99% of the spectral range when verifying randomness and obtainingthe final smoothed spectrum. The experience of the user, therequirements of the measurement, and the limitations of the computer arefactors that should be considered in the selection of the desired amountof the spectrum that should be smoothed. Furthermore, the width of theportions used in the fitting of the mathematical function (ormathematical functions, if more than one mathematical function isemployed) to the observed spectrum can be varied from spectral region tospectral region across the spectrum.

The method illustrated below is one procedure for determining a best fitto the spectral data to minimize the noise without distorting thespectral features that are to be observed. This method is a matrixoperation for a least squares fit. Other procedures, such as asum-and-difference method or a weighted least squares method can also beused.

In order to find the smoothed absorbance value a_(q), a matrix R_(q) isformed $\begin{matrix}\begin{matrix}{R_{q} = \begin{bmatrix}1 & \lambda_{q - {n/2}} & \lambda_{q - {n/2}}^{2} & \ldots & \lambda_{q - {n/2}}^{l} \\1 & \lambda_{q - {n/2} + 1} & \lambda_{q - {n/2} + 1}^{2} & \ldots & \lambda_{q - {n/2} + 1}^{l} \\1 & \vdots & \vdots & \vdots & \vdots \\1 & \lambda_{q} & \lambda_{q}^{2} & \ldots & \lambda_{q}^{l} \\1 & \vdots & \vdots & \vdots & \vdots \\1 & \lambda_{q + {n/2}} & \lambda_{q + {n/2}}^{2} & \ldots & \lambda_{q + {n/2}}^{l}\end{bmatrix}_{{n + 1},\quad {l + 1}}} \\{= \begin{bmatrix}r_{q - {n/2}} \\r_{q - {n/2} + 1} \\\vdots \\r_{q} \\\vdots \\r_{q + {n/2}}\end{bmatrix}}\end{matrix} & (14)\end{matrix}$

where

n represents the number of wavelengths to be included in the fit,

l represents the order of the polynomial that will be used in the fit,

λ_(q) ^(l) represents the q^(th) wavelength, of l^(th) order, and

r_(q) represents the q^(th) row vector in the R_(q) matrix.

The number of wavelengths to be included in the fit can be chosentheoretically or empirically. Theoretically, a good rule of thumb is touse a number of wavelengths commonly used in a statistical analysis. Forexample, 20 data points are usually used for calculating the averagevalue of a quantity under investigation. Empirically, a good number ofwavelengths to be used can be found by searching through a range ofnumbers, such as from 10 to 30. Because this matrix operation ismulti-dimensional, the search for optimal number of wavelengths can alsobe done in conjunction with the search for the order of polynomialfunction. A typical spectrum of a biological sample with wavelengthsfrom the ultraviolet region to the visible region to the infrared regionof the electromagnetic spectrum would include wavelengths from 190 nm to40,000 nm. The number of wavelengths used would be 40 if 20 data pointswere used for fitting of a spectrum having a 2 nm step resolution.

The measured absorbance values are used to determine the coefficients ofthe polynomial by means of the following three equations:$\begin{matrix}{\begin{bmatrix}a_{q - {n/2}} \\a_{a - {n/2} + 1} \\\vdots \\a_{q} \\\vdots \\a_{q + {n/2}}\end{bmatrix} = {R_{q} \cdot \begin{bmatrix}x_{0} \\x_{1} \\x_{2} \\\vdots \\x_{l}\end{bmatrix}}} & (15)\end{matrix}$

 A _(q) =R _(q) ·X _(q)  (16)

X _(q) =[R _(q) ^(T) ·R _(q)]⁻¹ ·R _(q) ^(T) ·A _(q)  (17)

where

X_(q) represents the q^(th) set of polynomial coefficients,

[R_(q) ^(T)·R_(q)]⁻¹·R_(q) ^(T) represents the Pseudo-inverse [see S. J.Leon, Linear Algebra with Applications, 2^(nd) ed., Macmillan PublishingCompany (1986)], and

A_(q) represents a column vector with the spectral absorbance centeredat the q^(th) wavelength, with n+1 elements.

The derivative spectrum can be smoothed in the same way. Higher order(second order and higher) derivatives can also be smoothed. Thederivative spectra can also be determined directly from the smoothedabsorbance spectra $\begin{matrix}\begin{matrix}{{\frac{}{\lambda}{\overset{\sim}{a}}_{q}} = {{\frac{}{\lambda}{r_{q} \cdot X_{q}}} = {\frac{}{\lambda}\quad \left( {x_{0} + {x_{1}\lambda} + {x_{2}\lambda^{2}} + {\ldots \quad x_{l}\lambda^{l}}} \right)}}} \\{= {x_{1} + {2\quad x_{2}\lambda} + {\ldots \quad {lx}_{l - 1}\lambda^{l - 1}}}}\end{matrix} & (18)\end{matrix}$

A commonly used method for removing high frequency random variation isby averaging absorbance values that are neighbors to an absorbance valueat a given wavelength. This method is known as box car averaging orrunning average smoothing. This method has the following disadvantages:

(a) reduction of peak height of spectral feature;

(b) distortion of spectrum by spreading spurious peak into wider areaand smearing the distinction between spectral features and noise peaks,which could lead to incorrect results;

(c) coupling the averaged value of noise into the signal, which couldcontribute to run-to-run variation and adversely affect the calibrationmethod.

Other methods such as low-pass Fourier filtering could work, but has thedisadvantage that the basis functions of the Fourier transform do notresemble the features of the underlying spectrum, consequently requiringhigh order terms in the fit, which terms contain noise and require moredata points to reduce the aliasing problem.

In a sample of urine, the analytes of interest include but are notlimited to glucose, ketones, creatinine, albumin, nitrites, urea,bilirubin, hemoglobin, and urobilinogen. Each of these analytes arenecessarily observed in a matrix containing many other analytes ofvarying concentration. The combination of the many analytes of nointerest in the matrix makes up a background upon which the analyte ofinterest must be observed. Because of the large number of analytes inthe background, the background may be varying and may be similar instructure to the spectral features of the analyte(s) of interest. Anyuseful data reduction method must be able to accurately quantify ananalyte of interest, the signal of which may possibly be small inmagnitude relative to the background.

FIG. 21 shows the derivative spectrum of a typical sample of urine. Thederivative spectrum is determined from an absorption spectrum of urine,and then smoothed by means of the techniques previously described. Thesmoothed derivative spectrum of water has been subtracted from thesmoothed derivative spectrum of urine. If it is assumed that thespectral features are due to urea, creatinine, glucose, albumin,ketones, and nitrites in this wavelength range, then the spectrum ofurine should be, after subtracting the water background,

S=L[c _(U) a _(U) +c _(C) a _(C) +c _(G) a _(G) +c _(A)a_(A) +c _(K) a_(K) +c _(N) a _(N)]  (19)

where

c_(U)a_(U),c_(C)a_(C),c_(G)a_(G),c_(A)a_(A),c_(K)a_(K),c_(N)a_(N)represent the products of the concentrations and absorption spectra ofurea, creatinine, glucose, albumin, ketones, and nitrites, respectively,and

S and L are as previously defined.

By means of a classical least squares fit, the concentrations(represented by c's in the above equation) can be determined if theabsorption spectra of the analytes of interest (represented by a's inthe above equation) are known (by independent measurement in acalibration step). FIG. 22 shows the spectrum of urine along with thespectral fit S. The spectrum of urine and the spectral fit are notperfectly superposed, which means that additional analytes other thanthe six mentioned contribute to the spectral signature of urine. Thedifference between the spectral fit and the spectrum of urine is calledthe residual spectrum. If the residual spectrum is not equal to zero, itis assumed that additional analytes or noise or both have not beenaccounted for. FIG. 23 shows the residual spectra of samples of urinefrom four different patients.

The similarity of the residual spectra from the four different patientssuggest that the residual spectrum is unlikely to be due to noise,because it is too consistent to be random. The residual spectrum istherefore more likely to be due to analytes other than urea, creatinine,glucose, albumin, ketones, and nitrites. Furthermore, this residualspectrum is very likely the result of summation of contributions frommany different analytes, each present in a small amount. It isimpractical to try to minimize the residual spectrum by including moreand more minor analytes in the measurement, because the number ofpossibilities is too great. Furthermore, there is no need to havedetailed account for the residual spectrum so long as the residualspectra are common among urine samples from different patients. Residualspectra can be compensated for by means of calibration.

The method of calibration must take into account the small fluctuationsin the backgrounds. If the backgrounds from one person's urine to thenext were completely different, then the ability to compensate for thefluctuating background would not be possible. However, it has been shownthat this is not the case. Several mathematical tools are available toquantify small changes in spectral features in the presence of moderatechanges in background signal. Among these tools are Partial LeastSquares (PLS), Principle Component Analysis (PCA), Classical LeastSquares (CLS), and Neural Networks.

The method contemplated herein for accounting for the residual spectrumin a biological sample can be described by the following steps:

(a) identifying at least one analyte that is a major component of saidbiological sample, said at least one analyte accounting for significantvariations with respect to a plurality of spectra of biological samplesfrom a plurality of donors of said biological samples;

(b) measuring a spectrum for each of the plurality of biological samplesfrom the plurality of donors of the biological samples;

(c) calculating a model spectrum for each of the plurality of biologicalsamples from the plurality of donors of the biological samples bymathematically fitting spectra of the analytes of the at least oneidentified analyte to each spectrum of each of the biological samplesfrom the plurality of donors of the biological samples;

(d) calculating a residual spectrum for each spectrum of each of thebiological samples from the plurality of donors of the biologicalsamples by subtracting each value of the model spectrum from each valueof the spectrum of the biological samples from the plurality of donorsof the biological samples that corresponds to the model spectrum;

(e) repeating steps (a), (b), (c), and (d) at least one time byintroducing at least one additional analyte to the model spectrum untilthe calculated residual spectra are substantially constant from onebiological sample to another biological sample of the plurality ofbiological samples from the plurality of donors of the biologicalsamples;

(f) determining a set of calibration parameters from the model spectra,said set of calibration parameters accounting for effects of saidsubstantially constant residual spectra; and

(g) using said calibration parameters to determine concentration of ananalyte of interest in the sample of biological fluid of the individual.

In order to simplify the understanding of the aforementioned method, atypical determination will be described. In the case of a urine sample,five analytes can be identified as major components of a urine sample.These analytes are creatinine, urea, glucose, protein, and ketones. Thespectrum for each of these five analytes, at unit concentration, areknown. To simplify the determination, it can be assumed that threedonors each provided a urine sample. The following symbols will be usedto follow the determination to the desired result:

Cc represents the concentration of creatinine

Cu represents the concentration of urea

Cg represents the concentration of glucose

Cp represents concentration of protein

Ck represents the concentration of ketones

Sc represents the spectrum of creatinine at unit concentration

Su represents the spectrum of urea at unit concentration

Sg represents the spectrum of glucose at unit concentration

Sp represents the spectrum of protein at unit concentration

Sk represents the spectrum of ketones at unit concentration

S1 represents the spectrum of the urine sample from donor no. 1

S2 represents the spectrum of the urine sample from donor no. 2

S3 represents the spectrum of the urine sample from donor no. 3

MS1 represents the model spectrum of a urine sample from donor no. 1

MS2 represents the model spectrum of a urine sample from donor no. 2

MS3 represents the model spectrum of a urine sample from donor no. 3

RS1 represents the residual spectrum of a urine sample from donor no. 1

RS2 represents the residual spectrum of a urine sample from donor no. 2

RS3 represents the residual spectrum of a urine sample from donor no. 3

Ccn represents the concentration of creatinine in the urine sample fromdonor no. n, where n=1, 2, 3

Cun represents the concentration of urea in the urine sample from donorno. n, where n=1, 2, 3

Cgn represents the concentration of glucose in the urine sample fromdonor no. n, where n=1, 2, 3

Cpn represents concentration of protein in the urine sample from donorno. n, where n=1, 2, 3

Ckn represents the concentration of ketones in the urine sample fromdonor no. n, where n=1, 2, 3

Pcm represents a calibration parameter for creatinine in the urinesample of a test subject

Pum represents a calibration parameter for urea in the urine sample of atest subject

Pgm represents a calibration parameter for glucose in the urine sampleof a test subject

Ppm represents a calibration parameter for protein in the urine sampleof a test subject

Pkm represents a calibration parameter for ketones in the urine sampleof a test subject

Sc, Su, Sg, Sp, and Sk are control spectra. They are measured byspectrometry. S1, S2, and S3 are measured from the urine samples fromthe donors. The model spectra are calculated from the followingequations:

MS1=(Cc1×Sc)+(Cu1×Su)+(Cg1×Sg)+(Cp1×Sp)+(Ck1×Sk)

MS2=(Cc2×Sc)+(Cu2×Su)+(Cg2×Sg)+(Cp2×Sp)+(Ck2×Sk)

MS3=(Cc3×Sc)+(Cu3×Su)+(Cg3×Sg)+(Cp3×Sp)+(Ck3×Sk)

The coefficients Ccn, Cun, Cgn, Cpn, and Ckn can be the least squaresfit of concentration creatine, urea, glucose, protein, and ketones,respectively, in the urine sample from donor no. n.

The residual spectra are calculated from the following equations:

RS1=MS1−S1

RS2=MS2−S2

RS3=MS3−S3

The foregoing calculations are repeated at least one time with at leastone additional analyte until RS1, RS2, and RS3 are substantially equal.The calibration parameters can be obtained by means of mathematicaloperations, such as, for example, simultaneous equations, which canfurther employ techniques such as classical least squares, partial leastsquares, pseudo inverse matrix operations, neural networks, and thelike. For example, Pc1, Pc2, and Pc3 can be obtained by a mathematicaloperation on MS1, MS2, and MS3 with respect to creatinine; Pg1, Pg2, andPg3 can be obtained by a mathematical operation on MS1, MS2, and MS3with respect to glucose; and so forth. The concentration of a givenanalyte in a urine sample from an actual test subject can be obtained bythe operation on the spectrum of the sample. For example,

Concentration of creatinine in sample=[S(1)×Pc1]+[S(2)×Pc2]+[S(3)×Pc3]+. . . +[S(m)×Pcm]

Concentration of glucose in sample=[S(1)×Pg1]+[S(2)×Pg2]+[S(3)×Pg3]+ . .. +[S(m)×Pgm]

where m is the number of elements in the spectrum

There is an optimal number of major components identified and accountedin an optical system. When that number is lower than the optimal number,the amount of variation remaining in the background is too great. Whenthat number is greater than the optimal number, the system is costly tobuild and there is a risk in over-compensating for the background. Onemajor feature of this invention is that the optimal number has beenachieved with a fixed number of identified major components, therebyleading to a stable residual spectrum for many samples of urine.Therefore, the residual spectra in the calibration process can beaccounted for in a manner similar to that used for subtracting a commonbackground.

Operation

The operation of a system constructed for practicing this invention isuncomplicated. Referring now to FIGS. 2, 3, 4, 5, 6, 7, 8, and 9A, abiological sample, typically in the form of a liquid, e. g., urine, isintroduced through the inlet port to fill the sample cell assembly andimmerse the pH electrodes. The assemblies for carrying out thespectroscopic measurement and the refractive index measurement areactivated and the measurements are read through the read zone of thesample cell assembly. pH is read simultaneously with the pH sensitiveelectrodes. All the foregoing steps of the operation are carried outunder the control of a microprocessor. The methods of making theforegoing readings are well known to one of ordinary skill in the art.After the readings have been taken, the biological sample is expelledand the system is ready for the next sample. The microprocessorprocesses the data collected and reports the result either asconcentration of an analyte of interest or as status of sampleadulteration. FIGS. 24, 27, 28, and 29 show the results of theperformance of spectroscopic assays for creatinine, glucose, nitrites,and urea, respectively.

There are at least two ways to expel the biological sample. The liquidsample can be pushed back through the inlet port to the originalcontainer or to a waste container. Alternatively, the liquid sample canbe further drawn through the sample cell assembly through the outletport to a waste container. The first way can employ a more compactinstrument, especially when dispensing liquid back to its originalcontainer. The second way requires a waste container. Although theinstrument might have to include additional weight to accommodate thewaste container, it has the advantage over the first way in that thecarry-over or cross-contamination problem is minimized.

Depending on the requirement for acceptable carry-over, there areseveral protocols for cleaning the sample cell assembly of theinstrument of this invention. In some cases, such as in a highthroughput screening operation, higher carry-over is tolerable astrade-off in favor of high-speed operation. Then, the residue from aprevious sample can be cleaned by using part of the immediatelysucceeding sample as a cleaning solution. Passing greater volume ofsample through the sample cell assembly can clean it by exchanging withthe residue from the previous sample. However, this method of cleaningis not very effective due to the low exchange rate in a high flow ratesituation. If even lower carry-over is desired, a protocol can be usedto enhance the cleaning efficiency with the succeeding sample. In thisprotocol, a few pauses or a short backward flow motion of a pipettingprocess can be included in the step of loading the sample cell assemblywith the sample through the inlet port. The reason that these additionalmotions are helpful in minimizing carry-over can be explained byprinciples of hydrodynamics. In a continuous flow situation, theaffinity between the wall of a tube, e. g., the inlet tube, and theliquid causes the flow of liquid in the tube to be greater along thelongitudinal axis of the tube than in any other area of the tube. Thisphenomenon is similar to the shear sheet flow of viscous liquid betweentwo parallel plates in a hydrodynamics model. The slower flowing liquidclinging to the wall of the tube becomes a contaminant for thesucceeding sample. To improve cleaning of the sample cell assembly, theshear sheet flow should be reduced to allow exchange of the fresh sampleand the residue of the previous sample clinging to the wall of the tube.The additional pauses or backward flow motions can counter thehydrodynamics of the shear sheet flow of the sample inside both the tubeand sample cell assembly. Less shear sheet flow will allow moreeffective mixing and therefore more thorough cleaning. The use of thisprotocol of a few pauses or a short backward flow motion typicallyresults in a sample containing less than 0.01% of a previous sample. Incases where minimal carry-over is important, a washing buffer could beincluded to wash the line and sample cell assembly. Wash buffer can beintroduced as blank sample between the liquid samples to provideadditional washing of the instrument. Alternatively, another way,washing buffer can be introduced into the fluid line by means of aswitching valve, thereby allowing high throughput.

The following non-limiting example will further illustrate the presentinvention.

EXAMPLE 1

This example illustrates an integrated system comprising a device thatis capable of not only performing reagentless urinalysis but also ofusing reagents when desired. The reagentless urinalysis system can becoupled to a system that uses reagents to further exploit the advantagesof the reagentless system. Protection of result integrity is a concernregardless of the diagnostic device employed. Result integrity could becompromised intentionally or unintentionally. Adulteration of urinesamples for drug-of-abuse screening is an example of intentional attackon the result integrity by the sample provider. Dilution of a urinesample by means of alcoholic beverage consumption or diuretic medicineuse is an example of unintentional compromise of result integrity. Amarker, such as creatinine, which does not break down or is notsignificantly filtered by the kidney into urine, serves well for markingchange of concentration of analyte as a function of change of urinevolume. Thus, the ratio of the concentration of an analyte of interestto the concentration of creatinine is a better indicator than theconcentration of the analyte of interest itself. For borderline caseswhere results could either be positive or negative, an analyte tocreatinine ratio value would be very useful as tiebreaker to assignsignificance to the result.

In a simple embodiment, a reagentless urinalysis system can be fittedeither to the front end of an analytical instrument or can be used as aparallel channel to the instrument. The front-end configuration couldassay the analytes on desired markers and determine whether it isbeneficial to expend the reagents for a clinical chemistry analysis. Theresults of a sample so screened would be expected to be accurate.Therefore, a front end configuration provides the greatest economicbenefit for reagent usage. However, such a configuration could delay theworkflow, because screening and assaying are performed sequentially. Ifhigh throughput is desired and cost of reagent is of little concern,then parallel processing for both the adulteration marker and theanalyte of interest would be more beneficial in term of reporting time.Results of analyte determination would be reported only if theadulteration channel indicated no adulteration. Reporting the ratio ofthe analyte of interest to creatinine along with determination ofcreatinine in the adulteration detection channel could be performedautomatically.

In a more complicated embodiment, a reagentless urinalysis system couldbe modified to include a reagent-using module in an integrated unit.Such a unit would have the advantage of reagentless performance for mostclinical chemistry analytes, while having the additional advantage ofhigh sensitivity for analytes present in trace amounts or analyteshaving high specificity, such as those determined by immunoassay. Forexample, a reagentless urinalysis system combined with immunoassay forHCG could provide better quantitation for diagnosis of an abnormal typeof pregnancy, ectopic pregnancy, where implantation occurred inside theFallopian tube instead of inside the uterus, as it should be. As anotherexample, a reagentless urinalysis system could be integrated with anassay for a given drug of abuse in a dedicated screening device forbetter reference and robust operation.

Several ways have been envisioned for integrating a system utilizingreagents with the reagentless system of this invention. As an example,in FIGS. 30A, 30B, and 30C, a reagent-using system comprises a container800 having a receptacle portion 802 in which a chemical reaction cantake place and a mouth 803 through which a biological sample can beintroduced. In FIGS. 30A, 30B, and 30C, the container 800 is a testtube. The test tube can be a conventional test tube made from glass or apolymeric material. At least one reagent 804, which can be in liquidform or solid form, for a specific assay can be sealed in a cap 806,which cap can be used to seal the container 800. The cap 806 is of asize and a shape that it can be conveniently inserted into the mouth 803of the container 800. The walls 807 of the cap 806 can be made fromglass or a polymeric material, preferably an injection-molded polymericmaterial. The top 808 of the cap 806 can be made of a pierceablematerial, such as, for example, metallic foil, polymeric film, orrubber, and the bottom 809 of the cap 806 can be made of a rupturablematerial, such as, for example, frangible glass, metallic foil, orpolymeric film. After the biological sample “U” is introduced into thecontainer 800 and the cap 806 is sealed to the container 800, thecontainer 800 is set in the assay instrument. A sampling probe 812 canpierce the top 808 of the sealed cap 806 and the shatter the bottom 809of the sealed cap 806 to release the reagent 804 into the biologicalsample “U” in the receptacle portion 802 of the container 800.Additional mixing to ensure complete dispersion of the reagent into thebiological sample can be accomplished by a few aspirating and dispensingoperations of the probe to wash the area containing the reagent(s). Thereaction mixture containing the biological sample and the reagent(s) caneither be read through the receptacle 802 or transferred to a readchamber. A variation with dried reagent in the bottom of a sealed tubeis also viable.

In another example, as shown in FIG. 31, a container 820 contains atleast one reagent 821, either in a dried form or in a liquid form, inreceptacle portions 822, 823, which are sealed with a rupturablemembrane 824. The rupturable membrane is preferably selected from glass,metallic foil, or polymeric film. Access to the reagent(s) can beachieved through the rupturable membrane 824 by a piercing probe (notshown). Dried reagent(s) can be reconstituted and the reconstitutedreagent(s) can be transferred by means of pipetting to a receptacleportion 826 where the chemical reactions occur. Liquid reagents can betransferred by means of pipetting to the receptacle portion 826 wherechemical reactions occur. The receptacle portions 822, 823 containingthe reagent(s) can be physically separated from the receptacle portion826 or they can be sub-compartments in a container 820 comprising aplurality of receptacle portions, as shown in FIG. 31.

In a still another embodiment, a reagentless read chamber could befitted downstream of an automated analyzer that uses a reagent. Afterthe chemical reaction with the reagent and the recording of its specificsignals have occurred in an automated analyzer in a conventional manner,the reaction mixture is passed along to the reagentless read chamber,where the visible spectrum and the infrared spectrum can be collected.One caution in using this arrangement is that the reagent used in theautomated analyzer should not have strong spectral features, becausethis would result in interference with the spectrum of the analyte ofinterest in the reagentless system.

EXAMPLE 2

This example illustrates an optical system and an integrated system fordetection of nephropathy. A reagentless urinalysis system can beemployed for many specific uses. One of such use involves detection ofnephropathy in a diabetic patient. As indicators for complications to adiabetic condition, the monitoring of kidney function is essential.Urinary micro-albumin assay together with urinary creatinine is acommonly used tool for this monitoring. Such assays are usuallyperformed in the physician's office as part of the quarterly orsemi-annual check up of the diabetic patient. The two analytes, proteinand creatinine, can be determined without reagents with the system ofthis invention. The system could employ infrared filter photometry. Afew well-positioned filters at wavelengths ranging from 1900 to 2500 nmcould determine albumin and creatinine and provide a useful ratio as anindex for a nephropathy indicator. For screening where high precision isnot necessary, a five-filter system can provide adequate performance.For monitoring where high precision is essential, more than five filterswould be preferred for reducing noise and improving performance.

EXAMPLE 3

This example illustrates an optical system and an integrated system fordetection of urea in urine. Another specific use of a reagentlessurinalysis system involves detection of urea in urine for monitoringkidney function for a diabetic patient. As an indicator forcomplications to a diabetic condition, monitoring of kidney function isessential. A high protein/low carbohydrate diet prescribed for adiabetic patients to control blood glucose level depends on the kidneyfunction to remove urea and uric acid, which are byproducts ofmetabolizing a diet containing a high amount of protein. A high urinaryurea concentration would be expected under these conditions. However, anoverly long time of being subjected to a high protein diet tends toinduce kidney damage. Therefore, it would be very useful for a diabeticpatient to check urinary urea level periodically and to adjust his dietto have more fiber and liquid to relieve the stress induced by a highprotein diet. A few well-positioned filters at wavelengths ranging from1900 to 2500 nm can be used to determine urea concentration accuratelyand precisely. A simplified version of a system using infraredderivative spectroscopy would be sufficient for this purpose. A multiplefunction integrated apparatus incorporating measurement of urea,creatinine, protein, and other analytes would also be useful for thediabetic patient. FIG. 27 is a diagram illustrating the performance of areagentless urea assay on a sample of urine. The reference value wasobtained by using diluted urine on a “VISION” instrument. Thereagentless method and apparatus of this invention showed goodperformance with good precision and high correlation to the referencemethod.

EXAMPLE 4

This example illustrates an optical system and an integrated system forurinary bilirubin determination for newborn. Another specific use for areagentless urinalysis system for determination of urinary bilirubininvolves monitoring hemolytic jaundice in the newborn. Significantnumbers of newborn babies suffer from excess bilirubin due to an immuneresponse to the blood type of the mother. Excess hemolytic reactionproduces a significantly high level of bilirubin, which could adverselyaffect the development of the baby. A blood bilirubin assay is usuallyused to monitor the development. The urinary bilirubin assay isnon-invasive in nature. Urinary bilirubin measurements are painless tothe baby and would be less likely to cause concern or heartache to thebaby's parents. An optical device having continuous monitoringcapability could track the clearance of bilirubin from the baby's systemeffectively. A simplified version of an instrument using visible lightderivative spectroscopy would be sufficient for this purpose. A multiplefunction integrated apparatus incorporating measurement of creatinine,protein, hemoglobin, and other analytes could also be useful foradditional information for tracking the baby's development. FIG. 32 is adiagram illustrating the performance of the reagentless bilirubin assayin urine samples. FIG. 33 illustrates the performance of an assay forhemoglobin in urine samples. The reference values were obtained bygravimetric spiking of bilirubin or hemoglobin into base urine samples.The reagentless optical method showed good recovery of the spiked amountwith high precision.

EXAMPLE 5

This example illustrates a smoothing process for reducing noise in anabsorption spectroscopy measurement. For simplicity, only a smallsegment of a spectrum of an actual urine sample was used. The wavelengthrange of this example begins at 450 nm and ends at 508 nm. The datainvolved 30 points. The wavelength increment between neighboring datapoints was 2 nm. A region comprising 15 data points and encompassing aspectral width of 30 nm was chosen for fitting. The fitting function inthis example was a polynomial function of second order, namely, aquadratic equation as shown in equation (13) above. In Table I, thefirst column lists the sequence number of each data point used. Table Ishows the wavelength in the second column and raw data of absorbance,recorded with a commercially available spectrometer, in the thirdcolumn. The numbered position of each column is read from left to right.The next six columns in Table I exemplify the values in the matrix to beused in the pseudo inverse operation that was set forth in equations(14), (15), (16), and (17), except each column has been displaceddownward three rows to illustrate its relationship to the original rawdata. The three-row shift in this example corresponds to a three datapoint contribution for the smoothed spectrum from each portion of rawdata. The coefficients of the second order polynomial function based ona least squares fit to each selected portion of raw data is shown inTable II. The value of the fitted second order polynomial function foreach portion of spectrum listed Table I was calculated with thecorresponding coefficients and is shown in the corresponding column inTable III. A smoothed spectrum, formed by collecting three data pointsfrom each spectral portion is shown in the tenth column of Table III.The residual spectrum, i. e., the difference of the smoothed spectrumand the non-smoothed spectrum, is shown in the eleventh column in TableIII. This residual spectrum represents the high frequency random noise.That this spectrum represents high frequency random noise can be isconfirmed in two ways: (1) absolute value for each data point in theresidual spectrum is low, and (2) the averaged value for all the datapoints in the residual spectrum, as shown in last row of Table III, isclose to zero. Random variation would be expected to provide a measuredvalue having about an equal chance of being higher or lower than truevalue, and the average of the differences should approach zero.

TABLE I Absorb- Wave- ance Portions of Spectral Region for Fitting withSelected Seq. length Raw Mathematical Function No. (nm) Data 1st 2nd 3rd4th 5th 6th 1 450 1.0469 1.0469 2 452 1.0148 1.0148 3 454 0.9855 0.98554 456 0.9582 0.9582 0.9582 5 458 0.9327 0.9327 0.9327 6 460 0.90660.9066 0.9066 7 462 0.8846 0.8846 0.8846 0.8846 8 464 0.8608 0.86080.8608 0.8608 9 466 0.8383 0.8383 0.8383 0.8383 10 468 0.8174 0.81740.8174 0.8174 0.8174 11 470 0.7972 0.7972 0.7972 0.7972 0.7972 12 4720.7770 0.7770 0.7770 0.7770 0.7770 13 474 0.7565 0.7565 0.7565 0.75650.7565 0.7565 14 476 0.7375 0.7375 0.7375 0.7375 0.7375 0.7375 15 4780.7183 0.7183 0.7183 0.7183 0.7183 0.7183 16 480 0.6999 0.6999 0.69990.6999 0.6999 0.6999 17 482 0.6821 0.6821 0.6821 0.6821 0.6821 0.6821 18484 0.6670 0.6670 0.6670 0.6670 0.6670 0.6670 19 486 0.6445 0.64450.6445 0.6445 0.6445 20 488 0.6282 0.6282 0.6282 0.6282 0.6282 21 4900.6110 0.6110 0.6110 0.6110 0.6110 22 492 0.5938 0.5938 0.5938 0.5938 23494 0.5755 0.5755 0.5755 0.5755 24 496 0.5581 0.5581 0.5581 0.5581 25498 0.5406 0.5406 0.5406 26 500 0.5222 0.5222 0.5222 27 502 0.50460.5046 0.5046 28 504 0.4883 0.4883 29 506 0.4720 0.4720 30 508 0.45720.4572

TABLE II 1st 2nd 3rd 4th 5th 6th x₀ 29.786 23.068 16.699 11.868 7.16358.6609 x₁ −0.1131 −0.0844 −0.0574 −0.0372 −0.0178 −0.024 x₂ 0.0001090.00007875 0.00005015 0.00002903 0.00000903 0.00001545

TABLE III Wave- Fitted Values of Selected Portions of Spectral Seq.length Raw Region No. (nm) Data 1st 2nd 3rd 4th 5th 6th SmoothedResidual 1 450 1.0469 1.0445 2 452 1.0148 1.0157 3 454 0.9855 0.9877 4456 0.9582 0.9606 0.9566 5 458 0.9327 0.9344 0.9317 6 460 0.9066 0.90900.9075 7 462 0.8846 0.8846 0.8839 0.8844 0.8846 −0.0001 8 464 0.86080.8610 0.8610 0.8625 0.8610 0.0002 9 466 0.8383 0.8383 0.8386 0.84100.8383 −0.0001 10 468 0.8174 0.8164 0.8169 0.8199 0.8164 0.8169 −0.000411 470 0.7972 0.7955 0.7959 0.7991 0.7965 0.7959 −0.0014 12 472 0.77700.7754 0.7754 0.7788 0.7768 0.7754 −0.0016 13 474 0.7565 0.7562 0.75560.7589 0.7573 0.7551 0.7589 0.0024 14 476 0.7375 0.7378 0.7365 0.73940.7381 0.7367 0.7394 0.0019 15 478 0.7183 0.7203 0.7179 0.7203 0.71910.7183 0.7203 0.0019 16 480 0.6999 0.7000 0.7016 0.7003 0.7000 0.70060.7003 0.0003 17 482 0.6821 0.6827 0.6832 0.6817 0.6818 0.6823 0.6817−0.0004 18 484 0.6670 0.6661 0.6653 0.6634 0.6636 0.6642 0.6634 −0.003619 486 0.6445 0.6478 0.6453 0.6455 0.6461 0.6455 0.0010 20 488 0.62820.6307 0.6275 0.6275 0.6282 0.6275 −0.0007 21 490 0.6110 0.6140 0.60990.6096 0.6104 0.6096 −0.0014 22 492 0.5938 0.5925 0.5917 0.5928 0.5928−0.0010 23 494 0.5755 0.5753 0.5739 0.5753 0.5753 −0.0002 24 496 0.55810.5584 0.5562 0.5578 0.5578 −0.0003 25 498 0.5406 0.5386 0.5406 26 5000.5222 0.5210 0.5234 27 502 0.5046 0.5035 0.5064 28 504 0.4883 0.4894 29506 0.4720 0.4727 30 508 0.4572 0.4560 Average = −0.00018

Various modifications and alterations of this invention will becomeapparent to those skilled in the art without departing from the scopeand spirit of this invention, and it should be understood that thisinvention is not to be unduly limited to the illustrative embodimentsset forth herein.

What is claimed is:
 1. An apparatus for measuring refractive index ofsample comprising: (a) a source of light capable of transmitting a beamof light through said biological sample; (b) a sample cell assemblyhaving a chamber for containing said biological sample, said chamberhaving a first window, a second window, a third window, and a fourthwindow, said third window and said fourth window perpendicular to saidfirst window and said second window, said third window parallel to saidfourth window, said first window not parallel to said second window; and(c) a detector, said source of light, said first window, and said secondwindow positioned such that a beam of light from said source of light iscapable of entering said first window of said chamber, is capable ofbeing transmitted through said sample, is capable of emerging from saidsecond window of said chamber, wherein said beam of light entering saidfirst window is not parallel to said beam of light emerging from saidsecond window and is not perpendicular to said first window.
 2. Theapparatus of claim 1, wherein said source of light is selected from thegroup consisting of a laser diode, light emitting diode, andincandescent lamp.
 3. An apparatus for measuring refractive index of abiological sample comprising: (a) a source of light capable oftransmitting a beam of light through said biological sample; (b) asample cell assembly having a chamber for containing said biologicalsample, said chamber having a first window and a second window, at leastone of said first window and said second window of said chamber beingcurved, whereby a beam of light entering said first window and exitingsaid second window is caused to focus at a focal point, said chamberfurther having a third window and a fourth window, said third window andsaid fourth window perpendicular to said first window and said secondwindow, said third window parallel to said fourth window; and (c) adetector, said detector positioned such that said beam of light forms aspot on said detector.
 4. The apparatus of claim 3, wherein said sourceof light is selected from the group consisting of a laser diode, lightemitting diode, and incandescent lamp.
 5. An apparatus for measuringrefractive index of a biological sample comprising: (a) a source oflight capable of transmitting a beam of light through said biologicalsample; (b) a sample cell assembly having a chamber containing saidbiological sample, said chamber having a first window and a secondwindow, said first window parallel to said second window, said chamberfurther having a third window and a fourth window, said third window andsaid fourth window perpendicular to said first window and said secondwindow, said third window parallel to said fourth window; and (c) adetector substantially adjacent to said second window, said beam oflight entering said first window not perpendicular to said first window.6. The apparatus of claim 5, wherein said source of light is selectedfrom the group consisting of a laser diode, light emitting diode, andincandescent lamp.